text:
|Publication number
|Publication type
|Application number
|Publication date
|4 Sep 2007
|Filing date
|16 Jul 2004
|Priority date
|24 Apr 2001
|Fee status
|Also published as
|Publication number
|M. Kivanc Mihcak, Ramarathnam Venkatesan
|Original Assignee
|Microsoft Corporation
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (88), Non-Patent Citations (36), Referenced by (7), Classifications (4), Legal Events (3)
|External Links: USPTO, USPTO Assignment, Espacenet
This application is a continuation of and claims priority to U.S. patent application Ser. No. 09/843,234, filed Apr. 24, 2001, now U.S. Pat. No. 6,996,273 the disclosure of which is incorporated by reference herein.
This invention generally relates to a technology for recognizing the perceptual similarity of the content of digital goods.
Creative content—such as music, imagery, video, film, and the like—is increasingly converted into an electronic form or stored in such a form. Often, such content is originally recorded (i.e., created) in an electronic form. More particularly, this electronic form is typically digital.
"Digital goods" is a generic label for electronically stored or transmitted content, such as creative content. Examples of digital goods include images, audio clips, video, multimedia, software, and data. Digital goods may also be called a "digital signal," "content signal," "digital bitstream," "media signal," "digital object," "object," and the like.
Digital goods are often distributed to consumers over private and public networks—such as Intranets and the Internet. In addition, these goods are distributed to consumers via fixed computer readable media, such as a compact disc (CD-ROM), digital versatile disc (DVD), soft magnetic diskette, or hard magnetic disk (e.g., a preloaded hard drive).
Digital goods offer many advantages over conventional analog media in terms of quality and ease of transmission. With the ever-increasing popularity of the Internet, digital goods have become a mainstay ingredient of the Web experience.
Unfortunately, it is relatively easy for a person to pirate the pristine digital content of a digital good at the expense and harm of the content owners—which includes the content author, publisher, developer, distributor, etc. The content-based industries (e.g., entertainment, music, film, etc.) that produce and distribute content are plagued by lost revenues due to digital piracy.
Modern digital pirates effectively rob content owners of their lawful compensation. Unless technology provides a mechanism to protect the rights of content owners, the creative community and culture will be impoverished.
In addition, digital goods are often stored in databases. As these databases grow, the needs for categorizing goods are becoming increasingly important. The next generation of database management software will need to accommodate solutions for fast and efficient categorization of digital goods and protection of copyrights in those digital goods.
Hashing techniques are used to protect the rights of content owners and to speed database searching/access. Hashing techniques are used in many areas such as database management, querying, cryptography, and many other fields involving large amounts of raw data.
In general, a hashing technique maps a large block of raw data into relatively small and structured set of identifiers. These identifiers are also referred to as "hash values" or simply "hash." By introducing a specific structure and order into raw data, the hashing function drastically reduces the size of the raw data into short identifiers. It simplifies many data management issues and reduces the computational resources needed for accessing large databases.
Mathematically, a hashing technique involves an implementation of a hashing function HK(�). That function takes a signal x as input and computes a short vector h=HK(x). That vector is an apparently random value, which is indexed by a secret key K, in some large set. That vector h is a hash value.
The use of hashing techniques are many and indeed wide-ranging: compilers, checksums, searching and sorting techniques, cryptographic message authentication, one-way hashing techniques for digital signatures, time stamping, etc. These techniques usually accept binary strings as inputs and produce a hash value having a fixed length L. Typically, these techniques use random seeds (i.e., keys) of some type.
The hash values produced by such techniques are viewed as useful because they typically have following desirable characteristics:
Conventional hashing techniques are used for many kinds of data. These techniques have good characteristics and are well understood. Unfortunately, digital goods with visual and/or audio content present a unique set of challenges not experienced in other digital data. This is primarily due to the unique fact that the content of such goods are subject to perceptual evaluation by human observers. Typically, perceptual evaluation is visual and/or audible.
For example, assume that the content of two digital goods are, in fact, different, but only perceptually insubstantially so. A human observer may consider the content of two digital goods to be similar. However, even perceptually insubstantially differences in content properties (such as color, pitch, intensity, phase) between two digital goods result in the two goods appearing substantially different in the digital domain.
Thus, when using conventional hashing functions, a slightly shifted version of a digital good generates a very different hash value as compared to that of the original digital good, even though the digital good is essentially identical (i.e., perceptually same) to the human observer.
The human observer is rather tolerant of certain changes in digital goods. For instance, human ears are less sensitive to changes in some ranges of frequency components of an audio signal than other ranges of frequency components.
This human tolerance can be exploited for illegal or unscrupulous purposes. For example, a pirate may use advanced audio processing techniques to remove copyright notices or embedded watermarks from audio signal without perceptually altering the audio quality.
Such malicious changes to the digital good are referred to as "attacks", and result in changes at the data domain. Unfortunately, the human observer is unable to perceive these changes, allowing the pirate to successfully distribute unauthorized copies in an unlawful manner.
Although the human observer is tolerant of such minor (i.e., imperceptible) alterations, the digital observer—in the form of a conventional hashing technique—is not tolerant. Traditional hashing techniques are of little help identifying the common content of an original digital good and a pirated copy of such good because the original and the pirated copy hash to very different hash values. This is true even though both are perceptually identical (i.e., appear to be the same to the human observer).
Furthermore, traditional hashing techniques are of little help recognizing similar content of two digital goods. This is true even when both are perceptually similar (i.e., appear to be similar to the human observer). With conventional hashing techniques, the resulting hash values of goods with perceptually similar content are apparently completely different with a high degree of probability.
Applications for Hashing Techniques
There are many and varied applications for hashing techniques. Some include anti-piracy, content categorization, content recognition, content-based key generation, and synchronization of video signals.
Hashing techniques may be used to search for digital goods on the Web suspected of having been pirated. Like anti-piracy, semantic categorizing of the content of digital goods often requires subjective comparisons to other existing digital goods. Works of a similar nature are typically grouped into the same category. The content of digital goods may be semantically classified into any number of categories.
In addition, hashing techniques are used to generate keys based upon the content of a signal. These keys are used instead of or in addition to secret keys. Also, hashing functions may be used to synchronize input signals. Examples of such signals include video or multimedia signals. A hashing technique must be fast because synchronization is performed in real time.
Background Conclusion
Quickly and efficiently determining a hash value of a digital good is highly desireable. In addition, doing so that one can determine perceptual similarity of the content of a group of digital goods would improve anti-piracy efforts and semantic content categorization. It can improve content-based key generation and synchronization in video signals.
Accordingly, what is needed is a new hashing technique. A new technique is needed to overcome the difficulties that are brought by conventional hashing techniques when they are applied to multimedia data. Under perceptually unnoticable changes, such techniques produce different hash values with high probability.
More particularly, a new hashing technique is needed where the hash values of digital goods are proximally near each other, when the digital goods contain perceptually similar content. Furthermore, such a new hashing technique may provide a significant step towards determining whether a particular specimen of a digital good is a pirated copy of an original good.
Moreover, these new techniques would improve existing content-based key generation, which is often employed in the watermarking. These new techniques would introduce improved synchronization so as to achieve synchronization in watermarking streaming multimedia data, such as video and audio
Described herein is a technology for recognizing the perceptual similarity of the content of digital goods.
At least one implementation, described herein, introduces a new hashing technique. More particularly, this hashing technique produces hash values for digital goods that are proximally near each other, when the digital goods contain perceptually similar content. In other words, if the content of digital goods are perceptually similar, then their hash values are, likewise, similar. The hash values are proximally near each other. This is unlike conventional hashing techniques where the hash values of goods with perceptually similar content are far apart with high probability in some distance sense (e.g., Hamming).
This summary itself is not intended to limit the scope of this patent. Moreover, the title of this patent is not intended to limit the scope of this patent. For a better understanding of the present invention, please see the following detailed description and appending claims, taken in conjunction with the accompanying drawings. The scope of the present invention is pointed out in the appending claims.
The same numbers are used throughout the drawings to reference like elements and features.
In the following description, for purposes of explanation, specific numbers, materials and configurations are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to one skilled in the art that the present invention may be practiced without the specific exemplary details. In other instances, well-known features are omitted or simplified to clarify the description of the exemplary implementations of present invention, thereby better explain the present invention. Furthermore, for ease of understanding, certain method tasks are delineated as separate tasks; however, these separately delineated tasks should not be construed as necessarily order dependent in their performance.
The following description sets forth one or more exemplary implementations of a robust recognizer of perceptually similar content that incorporate elements recited in the appended claims. These implementations are described with specificity in order to meet statutory written description, enablement, and best-mode requirements. However, the description itself is not intended to limit the scope of this patent.
The inventors intend these exemplary implementations to be examples. The inventors do not intend these exemplary implementations to limit the scope of the claimed present invention. Rather, the inventors have contemplated that the claimed present invention might also be embodied and implemented in other ways, in conjunction with other present or future technologies.
An example of an embodiment of a robust recognizer of perceptually similar content may be referred to as an "exemplary content similarity recognizer."
Incorporation by Reference
The following co-pending patent applications are incorporated by reference herein:
The one or more exemplary implementations, described herein, of the present claimed invention may be implemented (in whole or in part) by a content similarity recognition system 100 and/or by a computing environment like that shown in
At least one implementation is described herein as a technique for generally recognizing content of digital goods by hashing such goods to generate one or more hash values for each good.
At least one implementation is described herein as a technique for recognizing perceptual similarity of content of such goods by comparing "recognition" hash values of the goods. This implementation generates proximally similar (i.e., near) unique identifiers (e.g., hash value) even though some forms of alterations (including intentional and unintentional) have been done to a specimen of the original digital good, given that the altered specimen is perceptually similar to a human observer when comparing the altered specimen with the original specimen. However, if the altered specimen is perceptually distinct, the hashing technique produces a hash value that is not proximally near the hash value of the original.
At least one implementation described herein is a technique that may be combined with the techniques described in U.S. patent application Ser. No. 09/421,986, entitled "System and Method for Hashing Digital Signals" (incorporated by reference) to produce a unique identifier.
The implementations, described herein, may employ one of two exemplary approaches to generating a hash value: Approach A and Approach B. Approach A is particularly suited for applications where there is little or no concern about malicious attacks. Approach B is particularly suited for those applications where there is a concern about such attacks.
Isolated significant components of a signal are not robust. The exemplary content similarity recognizer applies non-linear filtering to eliminate such "spike-like" components. On the other hand, around big masses of significant data, the exemplary content similarity recognizer introduces artificial "blurred tolerance regions" to gain stability (in shape and size) against small differences between signals.
In general, attacks on signals tend to split, distort, bend, stretch, and translate the smaller masses more than the larger ones. The exemplary content similarity recognizer includes iterative and convergent techniques that introduce a self-correcting mechanism.
The description of the implementations of the exemplary content similarity recognizer are particularly directed towards digital goods that are images. Although that is the case, those who are skilled in the art understand and appreciate how to apply these concepts to other digital goods—such as audio, multimedia, video, etc.
Exemplary Applications
Implementations, described herein, of the exemplary content similarity recognizer are suitable for numerous applications, including the following (which are provided as examples and not as limitations): identification, searching & sorting in a database, semantic content categorization, and anti-piracy applications (such as watermarking). Some of the exemplary applications are discussed below:
Locating similar content in a database. The "recognition" hash values may be stored and associated with specific content of a digital good. When searching for such content, a search engine may look for a range of hash values to locate similar content. This is much more efficient that conventional techniques for searching for similar content in a database (which is typically based on keyword searches).
Semantic content categorization. This includes approximate matching of content between two digital goods. The hashing techniques of the exemplary embodiments have a "recognition" value, which can be used to compare if two given items are similar. This hash value may also be called a recognition hash value or simply similarity value.
This "recognition" value may be used to semantically classify content of digital goods. Works of a similar nature tend to have "recognition" values that cluster together. Thus, these values are proximally near each other. This proximal range may be subjectively determined. For some semantic categories, the range may be large and for others it may be small.
The "recognition" can be computed incrementally which means that if the exemplary embodiment slide the window of the digital good, one may compute the value on the new window from the old window without doing substantial reworking on the part that is common to old and new windows.
Anti-piracy search efforts. Using the hashing techniques described herein, one may search for digital goods on the Web suspected of having been pirated. In one way, a subject good may be suspected of being pirated because their "recognition" value is proximally near the "recognition" value of the original digital good. Further examination may be performed to confirm piracy.
In addition, the "recognition" values may be used for content-based key generation or synchronization of streaming multimedia, such as video or audio. In this sense, the "recognition" values provide a mechanism to exactly or approximately identify a subject signal as an original signal.
Perceptually Same and Perceptually Distinct
The exemplary content similarity recognizer treats two "perceptually same" digital signals as the same. Herein, a pair of digital goods are "perceptually same" when their final hash values are the same (alternatively, substantially the same).
This may also be called "perceptually identical," "imperceptibly indistinguishable," or other similar equivalent phrases.
For example, "perceptually same" audio signals include those that sound as if they are they are substantially same to the human ear. For another example, "perceptually same" images include those that appear as if they are they are substantially same to the human eye.
In contrast, a "perceptually distinct" digital goods is generally the converse of "perceptually same" digital goods. This may also be called "perceptually different" or "perceptually distinguishable".
Perceptually Similar
The exemplary content similarity recognizer treats two "perceptually similar" digital goods as goods that are similar. Herein, a pair of digital goods are "perceptually similar" when their "recognition" values are close in value (i.e., proximal).
Unlike conventional hashing techniques, the output (i.e., hash value) of the hashing techniques implemented by the exemplary content similarity recognizer is invariant when the content of digital goods are perceptually similar. Logically and mathematically, this concept may be explained in the following way.
Let X denote a particular specimen of a digital good (e.g., image, audio clip, etc.). Furthermore, let {circumflex over (X)} denote a modified specimen of this good, where this modified specimen is "perceptually similar" to X. Let Y denote a particular specimen of a digital good that is "perceptually distinct" from X. See the above section titled "Perceptually Same and Perceptually Distinct" and "Perceptually Similar" for more details on the meaning of such terminology.
Let L be the final length of the hash, and let HK(�) represent a hashing function that uses the secret key K. A normalized Hamming distance D(.,.) is used fro comparing two hash values which is the ration of the usual Hamming distance and the size of the imputes.
Given the above, these are the characteristics of the hash values generated by the hashing techniques implemented by the exemplary content similarity recognizer:
(Invariance under perceptual similarity may also be described as approximate invariance under small perturbations.)
Hence, in addition to uniform distribution on the hash values, the following is desirable for all possible different digital goods X,Y and for all possible acceptable modified (i.e., perceptually similar) versions of X, represented by {circumflex over (X)}:
D(H K(X),H K({circumflex over (X)}))=0; and
(with a high degree of probability)
The hashing techniques implemented by the exemplary content similarity recognizer may have two stages: Intermediate and Final.
Intermediate Stage
At the end of the intermediate stage, the exemplary content similarity recognizer obtains intermediate hash values (i.e., "recognition" values) having a length M, where M>>L and have the following separation property:
D(H K(X),H K({circumflex over (X)}))<T 1; and
with a high degree of probability, where 0<T1<T2<�.
The intermediate hash value may also be called the "content-similarity" hash value, "similarity" hash value, "similarity" value, or "recognition" value. The intermediate hash value is the value that may be used by the exemplary content similarity recognizer to determine "perceptual similarity" of the content of digital goods.
Final Stage
Given the intermediate hash value, the exemplary content similarity recognizer performs randomized (or pseudorandomized) lattice vector quantization to generate the final hash value. This final hash values has the properties mentioned above (regarding uniform distribution, pairwise independence; and invariance).
For more details on hashing relevant to the hashing techniques implemented by the exemplary content similarity recognizer, see U.S. patent application Ser. No. 09/421,986, entitled "System and Method for Hashing Digital Signals" (which is incorporated herein by reference).
Exemplary Content Recognizer
In general, the exemplary content similarity recognizer generates an irreversible compression of the digital signal that dramatically shrinks the input (i.e., the signal) while keeping the essence of the input.
The segmenter 110 obtains a digital signal 105 (such as an audio clip). It may obtain the signal from nearly any source, such as a storage device or over a network communications link. The segmenter 110 separates it into multiple, pseudorandomly sized and distributed segments. If the signal is an image, the segmenter 110 may separate the image into rectangles, which are pseudorandomly sized and pseudorandomly located within the image. If the signal is an audio clip, the segmenter 110 may separate the clip into rectangles (of two-dimensions of time and frequency), which are pseudorandomly sized and pseudorandomly positioned within the clip. The segments may be overlapping.
Segmenter does not necessarily separate the segments from the signal or from each other. It does not necessiarly remove the segments from the signal. Instead, it defines regions or portions of the signal. Those defined regions are the segments.
If Approach A (described below) is being employed, then the segmenter 110 is not necessary.
The transformer 120 obtains a digital signal, which may be a segment of the digital signal 105 (that has been segmented by segmenter 110). The transformer 120 puts the signal in canonical form using a set of transformations. Specifically, for image (for example), discrete wavelet transformation (DWT) may be employed since it compactly captures significant signal characteristics via time and frequency localization. Other transformations may be used. For instance, shift-invariant and shape-preserving "complex wavelets" and any overcomplete wavelet representation or wavelet packet are good candidates (particularly for images).
The transformer 120 also finds the DC subband of the initial transformation(e.g., subband of the DWT). This DC subband of the transformed signal is passed to the quantizer 130.
In general, the transformer gets a significant frequency subband. That may be a low or the lowest subband (e.g., the DC subband). The lower frequency subbands are suitable because they tend to remain relatively invariant after signal perturbation.
The result of this transformer is a transformed signal. When the subject is an image, an example of a suitable transformation is discrete wavelet transformation (DWT). When the subject is an audio clip, an example of a suitable transformation is MCLT (Modulated Complex Lapped Transform). However, most any other similar transformation may be performed in alternative implementations.
In the frequency domain, the quantizer 130 applies a multi-level (e.g., 2, 3, 4) quantization on the output of the transformer 120 to obtain quantitized data (e.g., binary data) given a Hamming weight for output. Of course, other levels of quantization may be employed. Various quantizers could be used as long as suitable distortion metrics (instead of Hamming metric) are available to control the global behavior of the quantized data. The quantizer 150 may be adaptive or non-adaptive.
The iterative geometric converter 140 applies (iteratively) order-statistics filtering, local smoothing (e.g., local averaging), and two-level quantization (given Hamming weight of output). Of course, other levels of quantization may be employed. More details regarding the function of the converter 140 are provided below in the discussion of Approaches A and B.
The segment combiner 160 collects the multiple, pseudorandomly sized and distributed segments (produced by the segmenter 110) to generate an output that is the "recognition" value 162 (i.e., intermediate hash value). The combiner then applies pseudorandom projection on the collected data.
If Approach A (described below) is being employed, then the segment combiner 160 is not necessary.
The functions of aforementioned components of the content similarity recognition system 100 of
Methodological Implementation of the Exemplary Content Recognizer
For both approaches, the hash values of separate inputs are compared to determine perceptual similarity. This may be done using normalized Hamming distance. Perceptual distortion metrics may be used as well.
Approach A
Approach A is particularly suited for applications where there is little or no concern about malicious attacks. This approach does not use a secret key and hence there is no pseudorandomness involved. Blocks 210, 212, and 214 are not performed for this approach.
At 216 of
At 220 and 222, the exemplary content similarity recognizer quantizes the transformed signal. The output of the quantizer is subject to iterative geometric conversion. The recognizer picks up the significant regions by thresholding (e.g., 2-level quantization). To gain robustness against modifications, the recognizer employs a simple iterative filtering technique that minimizes the presence of "geometrically weak components" and enhance the "geometrically strong components" by means of region growing.
A region that has isolated significant components (i.e., geometrically weak) is a good candidate to be erased via modifications, whereas a region that has massive clusters of significant components (i.e., geometrically strong) would probably remain. However, the location might be perturbed a little and the shape of the cluster could be varied slightly. Unlike the conventional techniques, the recognizer relies on the convergence of a self-correcting iterative procedure.
The number of potential limits for the set of all meaningful signals is large enough since the output is based on the geometric structure of the input signal. Due to the self-correcting nature of this function, the output of the iterative geometric conversion is probably a stable attractive point for the region of most possible slight modifications.
Let X represent the input signal, L be the number of levels DWT that is applied. Let W(x) be the normalized Hamming weight of any binary input x, which is the ratio of the usual Hamming weight and the size of the input. For a given two-dimensional matrix A, let A (i,j) represent the (ij)th entry of A.
Order-statistics filtering S[m,n],p(�): Given a two-dimensional input A, S[m,n],p (A)=B, where ∀i,j,B(i,j) is equal to the pth element of the sorted set of {A(i′,j′)}, where i′∈{i−m,i−m+1, . . ., i+m} and j′∈{j−n,j−n+1, . . . , j+n} (sorting is done in ascending order); here the term S[m,n],p(�) is the order-statistics filter. For order-statistics filtering to be equivalent to two-dimensional median filtering if, for example, for a window of size (2m+1)�(2n+1), then p is chosen as 2mn+m+n+1.
During geometric region growing, the exemplary content similarity recognizer also use linear shift invariant filtering via two-dimensional FIR filter f, which has low pass characteristics and introduces blurry regions around significant components.
The following is a continued description of Approach A with some reiteration of the above description:
Transformation. At 218, the exemplary content similarity recognizer finds the DWT of X up to level L. Let XA be the resulting DC subband.
Quantization. At 220, the exemplary content similarity recognizer performs a thresholding operation (e.g., 2-level quantization) on XA to produce a binary map M. The map M may be represented in this fashion: M(i, j)=1 if X(i, j)≧T or 0 otherwise. T is chosen such that the W(M)≈q, where 0<q<1 is a parameter.
Geometric Region Growing. At 222, the exemplary content similarity recognizer performs "geometric region growing" (i.e., "iteratively geometrical conversion"). Let M1=M and ctr=1.
Order-Statistics Filtering. It performs order-statistic filtering on M1. M2:=S[m,n],p(M1), where m, n and p are parameters.
Local Smoothing. It applies a two-dimensional linear shift-invariant filtering on M3 via filter f, where M3(i, j)=A M2(i, j); f and A are parameters. Let the output be M4.
Quantization. Apply a thresholding operation on M4. This operation is similar to the one performed in block 220. Let M5 be the output, such the W(M5)≈q and ctr=ctr+1.
The above order-statistics filtering, local smoothing, and quantization of block 222 are repeated (i.e., iterated) until ctr≧C. At that point, block 222 generates the recognition hash value H(X)=M5. Otherwise, for each iteration within block 222, the exemplary content similarity recognizer finds D(M5, M1); if it is less then ∈ (convergence achieved), then end the iterations and generate the recognition hash value H(X)=M5. If it is not less then ∈ (convergence not achieved), then set M1=M5 and ctr=ctr+1 and perform another iteration.
Instead, the reader is directed to notice the similarity of the visual representations of
Returning now to the description of the methodological implementation of Approach A, the iterative GRG (block 222 of
Approach B
Approach B is particularly suited for those applications where there is a concern about malicious attacks. This approach does use a secret key and hence there is pseudorandomness involved. This approach includes Approach A as a special case with no randomness and using largest segment possible in a one-segment initialization. All blocks of
At 210 of
These segments may be two-dimensional (or more dimensions) shape mapped onto a representation of the signal. Typically, representation and the segments have the same dimensions. The exemplary content similarity recognizer typically will generate a sufficient quantity of segments to adequately cover the representation of the signal.
For each segment, blocks 214-230 are repeated. Blocks 216-222 are performed in the same manner as Approach A, except that one segment is processed each loop through.
At 232 of
Contrast with Halftoning
Image halftoning produces a binary version of the input image, but where perceptual quality and similarity of the output is paramount. In other words, the results of image halftoning will and is intended to be perceptually approximate the original image. In contrast, output of the exemplary content similarity recognizer (or some subset thereof) is not necessarily related to the original representation. If the signal is an image, the output of the exemplary content similarity recognizer (or some subset thereof) does not necessarily look like the original. Of course, it may look like the original, but it is not a necessary requirement.
Exemplary Computing System and Environment
The exemplary computing environment 900 is only one example of a computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the computer and network architectures. Neither should the computing environment 900 be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary computing environment 900.
The exemplary content similarity recognizer may be implemented with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use include, but are not limited to, personal computers, server computers, thin clients, thick clients, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The exemplary content similarity recognizer may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The exemplary content similarity recognizer may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The computing environment 900 includes a general-purpose computing device in the form of a computer 902. The components of computer 902 can include, by are not limited to, one or more processors or processing units 904, a system memory 906, and a system bus 908 that couples various system components including the processor 904 to the system memory 906.
The system bus 908 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures can include an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnects (PCI) bus also known as a Mezzanine bus.
Computer 902 typically includes a variety of computer readable media. Such media can be any available media that is accessible by computer 902 and includes both volatile and non-volatile media, removable and non-removable media.
The system memory 906 includes computer readable media in the form of volatile memory, such as random access memory (RAM) 910, and/or non-volatile memory, such as read only memory (ROM) 912. A basic input/output system (BIOS) 914, containing the basic routines that help to transfer information between elements within computer 902, such as during start-up, is stored in ROM 912. RAM 910 typically contains data and/or program modules that are immediately accessible to and/or presently operated on by the processing unit 904.
Computer 902 may also include other removable/non-removable, volatile/non-volatile computer storage media. By way of example,
The disk drives and their associated computer-readable media provide non-volatile storage of computer readable instructions, data structures, program modules, and other data for computer 902. Although the example illustrates a hard disk 916, a removable magnetic disk 920, and a removable optical disk 924, it is to be appreciated that other types of computer readable media which can store data that is accessible by a computer, such as magnetic cassettes or other magnetic storage devices, flash memory cards, CD-ROM, digital versatile disks (DVD) or other optical storage, random access memories (RAM), read only memories (ROM), electrically erasable programmable read-only memory (EEPROM), and the like, can also be utilized to implement the exemplary computing system and environment.
Any number of program modules can be stored on the hard disk 916, magnetic disk 920, optical disk 924, ROM 912, and/or RAM 910, including by way of example, an operating system 926, one or more application programs 928, other program modules 930, and program data 932. Each of such operating system 926, one or more application programs 928, other program modules 930, and program data 932 (or some combination thereof) may include an embodiment of a quantizer, a segmenter, a combiner, a transformer, and an iterative-geometric converter.
A user can enter commands and information into computer 902 via input devices such as a keyboard 934 and a pointing device 936 (e.g., a "mouse"). Other input devices 938 (not shown specifically) may include a microphone, joystick, game pad, satellite dish, serial port, scanner, and/or the like. These and other input devices are connected to the processing unit 904 via input/output interfaces 940 that are coupled to the system bus 908, but may be connected by other interface and bus structures, such as a parallel port, game port, or a universal serial bus (USB).
A monitor 942 or other type of display device can also be connected to the system bus 908 via an interface, such as a video adapter 944. In addition to the monitor 942, other output peripheral devices can include components such as speakers (not shown) and a printer 946 which can be connected to computer 902 via the input/output interfaces 940.
Computer 902 can operate in a networked environment using logical connections to one or more remote computers, such as a remote computing device 948. By way of example, the remote computing device 948 can be a personal computer, portable computer, a server, a router, a network computer, a peer device or other common network node, and the like. The remote computing device 948 is illustrated as a portable computer that can include many or all of the elements and features described herein relative to computer 902.
Logical connections between computer 902 and the remote computer 948 are depicted as a local area network (LAN) 950 and a general wide area network (WAN) 952. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet.
When implemented in a LAN networking environment, the computer 902 is connected to a local network 950 via a network interface or adapter 954. When implemented in a WAN networking environment, the computer 902 typically includes a modem 956 or other means for establishing communications over the wide network 952. The modem 956, which can be internal or external to computer 902, can be connected to the system bus 908 via the input/output interfaces 940 or other appropriate mechanisms. It is to be appreciated that the illustrated network connections are exemplary and that other means of establishing communication link(s) between the computers 902 and 948 can be employed.
In a networked environment, such as that illustrated with computing environment 900, program modules depicted relative to the computer 902, or portions thereof, may be stored in a remote memory storage device. By way of example, remote application programs 958 reside on a memory device of remote computer 948. For purposes of illustration, application programs and other executable program components such as the operating system are illustrated herein as discrete blocks, although it is recognized that such programs and components reside at various times in different storage components of the computing device 902, and are executed by the data processor(s) of the computer.
Computer-Executable Instructions
An implementation of an exemplary content similarity recognizer may be described in the general context of computer-executable instructions, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments.
Exemplary Operating Environment
The operating environment is only an example of a suitable operating environment and is not intended to suggest any limitation as to the scope or use of functionality of the exemplary content similarity recognizer(s) described herein. Other well known computing systems, environments, and/or configurations that are suitable for use include, but are not limited to, personal computers (PCs), server computers, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, programmable consumer electronics, wireless phones and equipments, general- and special-purpose appliances, application-specific integrated circuits (ASICs), network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
Computer Readable Media
An implementation of an exemplary content similarity recognizer may be stored on or transmitted across some form of computer readable media. Computer readable media can be any available media that can be accessed by a computer. By way of example, and not limitation, computer readable media may comprise "computer storage media" and "communications media."
"Computer storage media" include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer.
"Communication media" typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as carrier wave or other transport mechanism. Communication media also includes any information delivery media.
The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared, and other wireless media. Combinations of any of the above are also included within the scope of computer readable media.
Although the invention has been described in language specific to structural features and/or methodological tasks, it is to be understood that the invention defined in the appended claims is not necessarily limited to the specific features or tasks described. Rather, the specific features and tasks are disclosed as preferred forms of implementing the claimed invention.
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|Citing Patent
|Filing date
|Publication date
|3 Jun 2009
|18 Mar 2014
|Apple Inc.
|Methods and apparatuses for a compiler server
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|14 Oct 2014
|Tyco Electronics Corporation
|Fiber optic closure
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|Audio classification method and system
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|Fiber optic closure
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|U.S. Classification
|International Classification
|Cooperative Classification
|European Classification
|10 Feb 2011
|Fee payment
Year of fee payment: 4
|9 Dec 2014
Owner name: MICROSOFT TECHNOLOGY LICENSING, LLC, WASHINGTON
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MICROSOFT CORPORATION;REEL/FRAME:034541/0477
Effective date: 20141014
|25 Feb 2015
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Year of fee payment: 8


text:
Saving Planet Earth
These slim fit legwarmers are made from 55% Hemp / 45% Fleece, featuring Hoodlamb's 'Satifur' lining, embroidered logo, ribbed cuffs top and bottom, three custom buttons and a ribbed panel extending the whole length of the rear enabling them to stretch over clothing.
Why not team them up with some fantastically warm ear muffs too?
Colours: Cream, Indigo, Brown & Black
Size: 50cm long
Packed Weight:315g
|100% Vegan, Breathable, Colourfast, Eco World, Pre-shrunk, UV Safe

subset: commoncrawl


text:
Obit of Mrs. Owen (Alice Cleary) Murtaugh 1913
From the Chatsworth Plaindealer
Died, at her home in Chatsworth, on Tuesday morning, June 10, 1913, at the advanced age of 87 years. Old age, superinduced by ________, was the cause of death. Funeral services were held at SS. Peter and Paul's church at ten o'clock Thursday morning, June 12. Solemn high mass was celebrated by Father Wm. Murtaugh, with Father Chas. O'Brien, of Penfield, Ill., as deacon; Father M.F. Foley, of Geneseo, Ill., sub-deacon; and Father W.J. Burke, of Chatsworth, as master of Ceremonies. Father F.G. Lentz, of Piper City, preached the funeral sermon. In addition the following priests were also present at the ceremonies; Father Weldon, of Holy Trinity church, Bloomington; Father J.F. Power, of Dwight; Father Flanagan, of Tolono; Father Madden, of St. John's church, Peoria; Father Thos. Fitzgerald, of Lewistown.
Friends were present from Chicago, Kankakee, Fairbury, Pontiac, Strawn, Cullom, Ashkum and Clifton. The remains were laid at rest in St. Patrick's cemetery, beside those of her husband. In the death of Mrs. Murtaugh another of the early residents of this locality is removed from the scenes, which she had witnessed from the time they were raw prairie and sloughs, through, the various stages of developement into the magnificent agricultural lands and prosperous villages that we enjoy today. When one realized that she had lived in this vicinity for almost fifty years, it is possible to appreciate in a degree the changes she had seen take place.
Miss Alice Cleary was born at Nana, Tipperrary county, Ireland, in the year 1826, and was the oldest of six children. She came to America in 1852. When first coming to this country she resided in the East and came to Wilmington, Will county, Illinois in 1859. In 1865 she was united in marriage at Wilmington to Mr. Owen Murtaugh. After marriage they located upon the farm near Cullom, which was their home for many years, later leaving the farm and moving to the city.
Three children were born to this union: Mary, who died March 24, 1889, Eugene, who died June 8, 1891, and Miss Alice, who resided with her mother and cared for her most tenderly and faithfully to the end. Mr. Murtaugh died in Chatsworth May 11, 1904. He was the father to two children by a former marriage: Rev. William Murtaugh, pastor of St. Patrick's church at Sheffield, Ill., and Frank, Murtaugh, of Chatsworth, and to these two children, as well as her own, Mrs. Murtaugh was a kind, loving and considerate mother and he death is sincerely mourned by them.


text: The gf and I go to our fencing club once a week. While we're there during class, I spend most of the half-hour warmup working thinking about the ofmgcute 20 year old with the really nice ass, splayed out on a bed, and me chowing down on her box. Yet I'm never more than 15 feet away from the gf. God damnit Happens every fucking year.


text:
Brick by Brick and Romantic Rock present
Punk Rock Karaoke with special guests
Sat · March 25, 2017
Doors: 8:00 pm / Show: 8:30 pmBrick by Brick
$13 adv & $16 day of
This event is 21 and over
*Online sales end at 6PM day of show unless otherwise noted. After that, limited tickets will be available at the door.https://brickbybrick.ticketfly.com/event/1438892/
Punk Rock Karaoke
The original deal since 1996. We play....YOU sing! Pick a song,we give you the lyrics.We call your name and voila! you are the singer in a punk rock band backed by the finest hand picked side men.
SKIPJACK has been on the forefront of the San Diego music scene since 1996. Starting with their debut release foundations ,launched them into popularity in the mid-1990's. After a two year hiatus SKIPJACK released letters from the frontline in 2009, which contains the now crowd favorites ,1959, and short life no regrets. in 2011 SKIPJACK teamed up with Luke pabich of good riddance to release a split EP with his other band (outlie). The split was released on the home lab entertainment entitled "born into it". To follow the release of the split, SKIPJACK released their strongest album to date, kill American radio. Now as 2012 comes to a close, SKIPJACK is eager to hit the studio and write the next album which is currently already underway. Now we hope to see you at a show, singing along!!!!
Venue Information:
Brick by Brick
1130 Buenos Ave
San Diego, CA, 92110
Brick by Brick
1130 Buenos Ave
San Diego, CA, 92110


text:
It doesn't matter if it's at the high school, college or even the NFL level, finding a top tier cornerback is one of the most challenging positions to fill for any recruiter.
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text:
Last week, I shared my finished and styled photo ledge Eddie and I made for our bedroom. Now I'm back to talk about how I made it so you can make your own!
We loved these ledges from ikea for their flexibility in changing out frames and decor, but wanted something longer (the longest ikea ones are 45″, and we wanted at least 60″). Here's what you'll need to make your own: Supplies:
- Lumber: 1×2, 1×3, and 1×4 in the length of your final shelf
- Primer (
- Paint ( is plenty, I used un-tinted white in semi-gloss)
- Screws (I used (6) 1.5″ #6 screws for assembly and (3) 2″ #6 screws for attaching to the wall)
- Wood putty
- Electric drill
- Paint roller & tray
- Putty spatula (like this)
Our home depot was actually out of 1x2s and 1x3s, so we actually got a 1×4 and a 1×6 and cut the 1×6 down to a 1×2, 1×3, and some leftover with our table saw. Once you've got the lumber, start by priming and then painting each piece. Then clamp them together, pre-drill, and screw to assemble. You can see how the pieces go together below:
My center board was noticeably warped, so we did lots of clamping. Note that you don't need to clamp the whole piece at once (I only have 4 clamps!). we started at one end, lined up the ends of the boards, and clamped about 6″ on either side of my screw (less on the ends, since you want to anchor the ends securely close to the edges) then pre-drilled, put in the screw, and moved the clamps.
We screwed the back (1×3) on first, and didn't worry about covering those screws since they'll be against the wall. When we attached the front, we made sure to sink the screws in past the face of the wood so we'd be able to cover them up.
Once everything was assembled, I sanded the wood around the screws on the front since there was a bit of tiny splintering. I then filled the holes with putty. After that dried (read your putty instructions, mine said two hours for deeper holes so that's how long I waited), I sanded the putty even with the wood finish and painted over it.
Voila – seamless photo ledge! To attach it to the wall, we first found the studs and marked them vertically with painters tape. Then we lined up the shelf where we wanted it – cenetered over the headboard and at a height we liked. We attached the shelf to a stud on one end with the drill at an angle so the screw is below the front lip of the shelf – this makes the screw invisible from the front. We then used a level to make sure it was nice and flat, and attached the shelf to two more studs in the same manner.
Here's the whole thing with all the decorations I have up there for now:
And here's where you can find tutorials to the projects in that image that I've made myself and shared on the blog:
- Tufted headboard (part 1 and part 2)
- Table lamps from glass vases (and hidden monograms!)
- Easy watercolor trees
- Fabric covered monogram (coming soon!)
- Stenciled 'watercolor' canvas
- Yarn ball shadowbox


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From Rankin Road and Imperial Valley Dr, Houston, T, drive west on Rankin Road toward Rankin Cir E. Make a left turn onto Northborough Dr. Thicket Apartments will be on the right.
The Thicket is an exceptional gated apartment community in Huston offering one and two bedroom apartments. This affordable community is a pet friendly community allowing pets up to 20 pounds. Each of the apartments have air conditioning, vaulted ceilings, built-in book shelves and walk in closets. Select apartments have fireplaces. These spacious apartments also offer private patios or balconies, outside storage areas, and have energy efficient appliances.Community amenities for the Thicket include two large swimming pools and deck areas, 24 hour on-site maintenance, and a laundry facility. This quiet community is located close to schools, medical facilities, shopping, dining, and entertainment. Public transportation is located near the community entrance, and commuters will have easy access to area highways and Interstates.


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Nebraska is a great place to rent self-storage units and you will find that the most populated cities in Nebraska like Omaha, Lincoln, Bellevue and Grand Island, will provide you with the best selection. In these cities you will find sometimes hundreds of storage facilities within city limits. Rent your extra space storage units Omaha for free at these facilities and get great service and savings.
Find a Omaha storage facility, compare Omaha storage unit sizes, prices, amenities and discounts. View pictures, descriptions, and read customer reviews to assist you in making a selection. Once you select the public storage unit in Omaha that best fits your needs, simply reserve online for free and lock in your storage unit price, save money and time. If you prefer, you can call and speak to a friendly and professional customer service representative, who could answer all your questions and who could take a reservation over the phone for free. No credit card is required to reserve storage units in Omaha online or by phone. A detailed confirmation e-mail will be automatically forwarded to your inbox. Your storage unit will be available for you when you arrive at the self-storage facility on your move in date. Finding public storage In Omaha, or in nearby cities located in Papillion, Carter Lake, Council Bluffs or in Ralston is that fast, easy and affordable.
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Public Storage facilities in Omaha, NE offer a variety of discounts to their customers. When searching for storage units Omaha, compare the price of the storage unit as well as the discount that storage facility is offering on that unit. Some self-storage facilities offer the same special on every storage unit they have in their inventory, while other facilities might offer different specials on selective storage units in their inventory. Omaha storage facility specials change from day to day, depending on the storage facilities occupancy of a particular storage unit at that given time. Some storage facilities might not offer a discount on a storage unit.


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Rishita Manhattan – ...
₹ 4,000,000.00
₹ 7,800,000.00
Sobha Silicon Oasis is Pre Launch Project of Sobha Developers which is situated at Very Fine Location of Bangalore that is Electronic City Bangalore, Sobha Silicon Oasis is New way of Life which Offers 2BHK and 3BHK Spacious Residential Apartment which Covers all the Significant Facilities in the Apartment, This Housing Project Specially designs for the Secure Investment in the Real estate Market which Make Your future bright, Sobha Silicon Oasis Bangalore also Easily Linked with All the Main area of Bangalore and the USP of Sobha Silicon Oasis Bangalore Project is Proximity to the IT hub of Bangalore and Shopping Malls and all other Link is Closeness to this Residential Project, So if You Want to be Live in Bangalore then Sobha Silicon Oasis is Perfect Choice for you which Make your Life More Royal and Comfortable.
For more details visit @ - http://www.sobhasiliconoasis.in
Published date:
21/05/2016 1:02 pm
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City area:
Electronic City
Sarjapur Road, Electronic City, Bangalore
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Rishita Manhattan – ...
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Iran do Espírito Santo
Click here to learn more!
Iran do Espírito Santo's cast concrete Playground is an interactive monumental sculpture that was created in 2013, and was originally installed in Central Park. For Playground, this new location at The Fields Sculpture Park provides an incredibly different environment for the viewer to experience this work. This sculpture now exists in a space with copious amounts of open skyscape, large fields and stretching treelines that contrast immensely with the previous location that was surrounded by people, buildings, and traffic.
Playground, 2013


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Ever wonder where the Marshmallow comes from? Well I did. I decided to do a little research.
Did you know that the Marshmallow is considered a candy? I didn't. Surprisingly it dates back to Egypt, about 2000 BC. The ancient Egyptians are believed to have discovered a wild herb growing in marshes from which a sweet substance could be extracted and made into a very special confection reserved only for the pharaohs and gods. The Egyptians used a honey based candy and thickened it with the sap of the marsh mallow plant (althea officinalis) hence the name marshmallow.
Between 2000 BC and the 19th Century, not much happened in the Marshmallow world.
But in the mid 19th century, candy makers in France combined the sap with egg whites and sugar and whipped by hand into this yummy confection. As the popularity of marshmallows grew, candy makers in Europe needed to find a faster process than hand making the treat. The starch mogul system was developed allowing candy makers to heat a mixture of marsh root, sugar, egg whites and water and pouring into molds made of cornstarch.
Like many of our foods, it was also used as medicine. Now I can handle this kind of medicine (with a little chocolate and graham crackers - oh I got off track here, apologies). Doctors also extracted sap from the root of the plant, cooked it with egg whites and sugar and whipped it into a meringue that hardened into a medicinal candy to soothe sore throats, suppress coughs, and heal enhancer wounds.
In 1948, Alex Doumakes (son of the founder of Doumak, Inc., the makers of Campfire Marshmallows) patented the "extrusion process" which vastly revolutionized marshmallow production – making it fast and efficient. The process involves taking the marshmallow ingredients and running it through tubes. Afterwards the ingredients are cut into equal pieces, cooled, and packaged. Thanks to Alex's invention, marshmallows became an everday sweet treat and favorite ingredient for many recipes. (Alex HAS to be camp fire aficionado's personal heroes).
The marsh mallow plant, scientifically known as Althea officinalis, is an herb that grows in salt marshes and on the banks of large bodies of water. It is native to Asia and Europe and naturalized in the eastern United States. (Now, don't go out searching for the marsh mallow plant and eat the wrong thing!)
History of the S'More
No one really knows the origin of toasting marshmallows., however, the 1927 Girl Scout handbook (ha - we beat the Boy Scouts at something!) was the first to document the recipe of combining graham crackers, chocolate and toasted marshmallows. The name s'more is also a mystery…but we know it means… WE WANT S'MORE CAMPFIRE MARSHMALLOWS!!
Historia de Victuals means "history of food" in Latin
"Food history is as important as a baroque church. Governments should recognize cultural heritage and protect traditional foods. A cheese is as worthy of preserving as a sixteenth-century building." Carlo Petrini, the founder of the International Slow Food Movement
Monday, August 30, 2010
Today, August 30, is Toasted Marshmallow Day
Posted by Carol Casey at 7:05 AM
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|11 Dec 2013
I just did a CPU swap with a W7 OEM machine. No issues, save for the need to reactivate. Which might have been b/c I also swapped the MB.
One thing to keep in mind - RAM. If the i7 chip has a max memory of 64 bit, and the i5 a max of 32, and if you have more than 32, you will either a) wind up with 32, or b) run into some issues. Not sure which, tho....
I think what will happen for example 64 gigs on an i5 it'll just address 32 gigs and ignore the rest.
|My System Specs
|12 Dec 2013
Windows 10 64 bit
Memory is not a problem. My current i7 system has 16GB and the i5 has 8GB. But, both are Z77 motherboards and capable of more than 16 GB. After the switch and I make sure the OS is activated, I'll also swap memory.
|My System Specs
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partitions can affect performance?
dividing you HDD into many partitions would affect your performance?
|Performance & Maintenance
Will Different frequency ram affect Hdd ?
Recently, I added a new ram to my laptop with different frequency .one of it is 1333Hz and another is 1066Hz.After a few days , my computer hard disk is having bad sector , and ended up changing a new hard disk.Just wondering if the ram which caused the problem or it is just coincidence? :(
|Hardware & Devices
Does IE9 affect Windows Mail?
I am running Windows Mail (from Vista) with W7 x64 and it's been running fine. I am not sure if it's related or not, but I installed the IE9 RC on my laptop a few days ago, and I now notice that the message area info bar with the TO, FROM, Attachment Paperclip, and 'Click here to see images" is now...
|Browsers & Mail
Does Virus Affect Other Partition?
This may be a silly question, but does virus affect other partition? Just wondering.... I don't want my Mac OS X (Snow Leopard 10.6.6) partition (HFS+) on my 2006 Discrete Macbook Pro to be affected by a virus. (Bootcamped with Win 7 Pro x86) I have googled looking for a solution, but I...
|System Security
DirectX9 AND 11..affect anything ?
I attempted to install Need For Speed Most Wanted, and it said I didn't have DirectX. I've read to install DirectX9, but I'm afraid it can alter my DirectX11. Battlefield 1942, ePSXe emulator, it has been frustrating making all my classics run fine. I'm on 64-bit OS before anyone provides the...
Is this going to affect my performance?
It comes to system ratings. I have installed Windows 7 Release Candidate Build 7100, and one of my system ratings has changed...for the worse. 3D Business and gaming graphics performance Windows Vista: 3.3 Wi7 Beta 7068: 3.4 Wi7 RC1 7100: 3.1 Is this going to affect my gaming...
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The Pere-Lachaise Mystery : The Second Victor Legris Mystery Paperback
by Claude Izner
Part of the A Victor Legris Mystery series
In Paris 1890, Lady's maid Denise le Louarn fears the worst when her mistress, Odette de Valois, vanishes from the Pere-Lachaise cemetery during a visit to her husband's grave.
All alone in the great metropolis, Denise knows just one person she can go to for help: Odette's former lover, Victor Legris.
When the frightened girl turns up at his bookshop and tells him her story, Victor feels there must be a simple explanation for Odette's disappearance.
But as he begins to look into the matter, it soon becomes clear that something sinister lies behind events at the Pere-Lachaise.
- Format: Paperback
- Pages: 306 pages
- Publisher: Gallic Books
- Publication Date: 01/10/2007
- Category: Historical mysteries
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Showing 1 - 1 of 1 reviews.
Review by Cassandra2020
The Pere Lachaise Mystery by Claude Izner - good

Now this was the book I wanted to read when I picked up the first three in the series. The first one I found disappointing. This one was much better and vindicated my original choice.

This is the second in a series of mystery (possibly 'cosy' genre) novels set in Fin de siècle Paris featuring Victor Legris, a bookseller, and his various family and friends. A much better mystery and possibly a better translation as it was less clunky than the first book.

Victor's ex-mistress has been widowed and then mysteriously disappears. Her maid runs to Victor for help and initially he ignores what she is saying, presuming that his ex-mistress is away on a tryst of some nature. Regardless he agrees to help the
girl, but when she too disappears he gets involved in the mystery.

Not great literature, but a pleasant enough read and much better than the first one. I have less qualms about reading the third (currently on mount TBR) at some point in the future.
Also by Claude Izner | View all
Also in the A Victor Legris Mystery series | View all


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i found , no stumbled, across Canada Dry Bitter Lemon today at the local Genuardi's!! (NJ)haven't cracked it open yet but with another 98 degree day expected tomorrow, i will !!
not sure if it's as good or even comparable to Schweppes, but since that ship has sailed i'm open to another brand....any suggestions?


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Prestigia's customer service stays at your service 24/7 to answer to all your requests by phone or mail.
You can email us at : email@example.com or call us at the following numbers:
The hotel complex Amphitrite Palace Beach Resort is nestled on a private beach, facing the sea. The hotel was designed by the Mexican architect Josélis...
459 reviews


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|18 and Over Timed 10K
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|Stay In Bed
Jim Grahlman had always been extremely active - biking, golfing, running - he did everything. He even said a time or two "Running is terrible... but I like the stopping". Jim's symptoms began in his 40's with what appeared to be 'Parkinson's-like'. These symptoms progressed and he was diagnosed with HD in 2001, at the age of 59. Eventually Huntington's disease began changing the way Jim lived his life. The progression of his symptoms may have taken away his ability to do the activities he once loved but it has not changed his fun-loving spirit! His daughter, Michelle, at the age of 27, also made the choice to be genetically tested (because there is a 50/50 chance of inheriting this disease) and was informed that she was also gene positive. This is when she decided to, like her dad, get moving! Michelle says "Dad can't run anymore but I can." So we are doing this to remind her, him and everyone effected by this disease that we love and support them. Not every day do we feel like running, walking, exercising or sometimes even just getting out of bed.....but we can......so we do! Join us in celebration of strength like no other!
Want to connect with your frends and family and get more on this event? Check us out on Facebook!
A special thanks to our event partner:


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Keepin' It Green: The Week in DIY: Sustainable Ski Trips, Easy (and Green) Ways to Avoid Holiday Weight Gain, and More
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|The Week in DIY: Sustainable Ski Trips, Easy (and Green) Ways to Avoid Holiday Weight Gain, and More
Each week, we highlight some of our favorite projects from our friends at Treehugger and Planet Green to help inspire your inner DIYer.
8 Benefits of Home Cooking
Putting together dinner after a long day at work isn't always fun, but these unexpected pros of home cooking may change your mind.
Hit MindBodyGreen Travel for Hot Deals on Healthy Get-Aways
Escape dreary winter weather — without blowing your budget — by taking advantage of the sweet, sustainable trips on MindBodyGreen.
Which Children's Books are Destroying Precious Rainforest in Indonesia?
The Rainforest Action Network's new guide helps parents figure out which publishers are contributing to deforestation — and which aren't.
BPA in Canned Foods: The Best and Worst Brands Out There
Check this handy guide to quickly reference which brands are the biggest offenders when it comes to BPA.
7 Ways to Not Gain Even One Pound this Holiday Season
From Thanksgiving turkey straight through to your New Year's Eve champagne, the holiday season is full of weight-gain traps; avoid them with these green tips.
Top 5 Most Powerful Vegans
See which successful politicians, media players, athletes, and business owners are going meat-free.
Protect Your Pucker with This Bittersweet Chocolate & Orange Lip Balm
Avoid the dry, chapped lips of winter with this homemade — and delicious — chocolate-orange lip balm.
The 10 Best and Worst Ski Destinations for the Eco-Conscious Skier
Choose sustainable slopes in Colorado, Utah, California, and Idaho for this year's ski trip.
FInd 14 Uses for Orphan Socks
From pet beds and chew toys to homemade puppets and erasers, single socks get a new life with these easy projects.


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The Zanesville Muskingum County Port Authority is looking to possibly redevelop older properties in the city or county.
The project is still in the early phases. Right now the Port Authority is identifying key properties that have potential to be redeveloped but may have environmental contamination.
"We spent the majority of the meeting talking about whether or not we should apply for some Brownfield Assessment money," said Executive Director of ZMCPA, Mike Jacoby. Either the state government or federal government, can provide some grant money to do testing of properties that may or may not have an environmental contamination. They are typically old industrial sites or buildings."
Brownfields are plots of land, that have been used before and may need extensive clean up, due to possible contamination. During the meeting, Port Authority Board Members decided to apply for grant money to do the testing, but at this point it is not site specific.
"We talked in executive session, about some properties that might make sense, we are really not ready to talk publicly about that yet because we have no idea if the property owners have any interest at this point and we don't want to speculate some of these properties may be contaminated, when really they are not," explained Jacoby. "So it would be unfair to those property owners, to suggest that their property is contaminated."
Jacoby says the Port Authority Board has not decided whether to apply for clean up money or not, until they investigate the potential properties and approach the owners.


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So I said that I'm happy being a code monkey whom is told what to do and goes about doing said task at hand with the best quality possible. But I also made mention to the creation of tools for developers and programmers to use to improve productivity and ease.
I've had some experience working with electron which allows the creation of local web programs that work with Node.js. If you haven't guessed, I've been working with Node quite a log recently.
I used electron to create an app for some moderators on a discord server so they can see all the users, some information on them and comments from other moderators about said members. They could also see analytic information captured by the bot such as activity levels of every channel, when a user last sent a message to a channel in the server. The app was great for finding out information that discord doesn't support.
So learning more about electron or other similar apps that allow this kind of cross platform compatibility would help with my career and open up more opportunities to work in. So, I have some extended homework over the next 2 months...


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It's that time of year again, folks. There will be costumes to make, candy to buy, parties to arrange… where do you begin? Well, whether you're stressing about how to decorate your home for the annual Halloween party, or your kids are bugging you to find a pumpkin carving template, Mom Prepares can help YOU prepare for Halloween! In the following weeks, we'll be posting information about Halloween costumes, crafts, food, safety tips, decorating, and more, so stay tuned!
Make Your Own Halloween Costumes
Goody bag – Check. Cell phone – Check. Neighborhood map – Check. What's missing when you're on the way to a Trick-or-Treat adventure? Costumes! An essential part of Trick-or-Treating, a Halloween party, or a Reformation Day party (Reformation day celebrates the reformation movement in the church) is your costume. Now, there are two ways to get a fabulous costume – you can buy one, or make it yourself. For all of the moms looking to save money this Halloween, no-sew costumes and making costumes with stuff around the house are the way to go. Above all, do *NOT* buy face paint from the store, because it has all kinds of toxic stuff in it. Instead, make your own face paint and keep your kids skin healthy and safe. (Plus, who doesn't like getting their hands dirty? Invite your kids to help you make their costume paint!)
Halloween Goodies for Ghosts and Ghouls alike!
Looking for easy, but delicious treats for a Halloween party or get-together? You can stop looking – your party will be a hit with the Mom Prepares' Halloween specialty – I call it the Candycorn Smoothie. A mixture of pumpkin-caramel smoothie and Cool Whip, this treat will get your guests coming back for more. Oh – and don't forget the October staple – Baked Apples. A perfect midnight snack or bedtime dessert, hand them around whole or cut them into bite-sized pieces for delicious finger food. Last but not least, Halloween cookies are a must-have whether you host a party or have a Halloween potluck (or you feel like having a snack in the middle of the night). Easy to make, easy to bake, you won't regret whipping, blending, baking and mixing these fabulous Halloween treats!
Making the Most of Harvest Time
October isn't just about Halloween – it's also Harvest Month! That means it's time to get our your baskets and drive (or walk) down to your local orchards or gardens to pick your fresh apples and pumpkins. But wait – once you've picked the best of the harvest, what do you do with it all? Well, apples are perfect for apple pie, baked apples and apple dumplings. As for pumpkins, pumpkin pie is always a hit at my house, and you can't go wrong with pumpkin bread. Whether your taste runs to apple dumplings or pumpkin smoothies, Mom Prepares has your October needs covered!
What's your favorite part of October: Harvest time or Halloween, or Reformation Day?


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White Brown Horses HD Wallpaper
This White Brown Horses HD Wallpaper has recently added in Stylish HD Wallpapers. You Can search more about Horses and can get Free HD wallpapers, Widescreen wallpapers, 3D Wallpapers, Desktop Wallpapers, Tablet wallpapers, Iphone Wallpapers, Mobile Wallpapers and Photos, Images. To Download this High Definition HD Wallpaper of Horse as wallpaper background for your desktop, Click on image to enlarge and Download it to your Computer.
Find More HD Wallpapers OR 3D WideScreen Wallpaper about Horses in Stylish HD Wallpapers.
Category : Pets
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Tags: animals, brown horse, horses, white horse


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This story was written by E. E. Smith
This part is called, 13 Chapter 13 - Spacehounds Triumphant
Read by Mark Nelson
Download the show
Sci Fi Serial gives you your daily dose of Science Fiction. Each day we present you with a reading of a classic short story or one chapter from a book that is presented serially. Our aim is to help you fend off the boredom of your daily commute.


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Backmount (51 Votes)
Sidemount (64 Votes)
Backmount rebreather (34 Votes)
Sidemount rebreather (14 Votes)
no mount (10 Votes)
Switching from backmount to sidemount (8 Votes)
Switching from sidemount to backmount (1 Votes)
Yes, i own my own analyzer(s) (117 Votes)
No, i just use the shops or buddies (10 Votes)
I don't analyze (2 Votes)
Yes (43 Votes)
No (8 Votes)
I just noticed that all the posts by the inverted_bear have been removed from this thread.
Weird, especially since all the posts quoting his (now removed) stuff are still there.
In case someone...
Ok the mako scooter price has dropped. The extra batteries are sold and so is the carry case. 600 plus shipping now.robohips 11-20-2017 10:45 AM
Months? The last time I looked the IUCRR didn't have any reports after 2008.bamafan 11-20-2017 10:38 AM
**Salerno's !JE 11-20-2017 10:37 AM
Now you see why I have stayed away from CDF.shellmoundal 11-20-2017 10:21 AM
Not to derail from the gas planning/math debate, but I agree. There is almost never an "official announcement," even though investigatory reports and autopsy results are public record in Florida and...Six Feet Under 11-20-2017 10:10 AM
"Having said that.. out of interest.. madax is your every 2k buddy bottle recomendation the same for Ginnie and lets say EN?"
Nope, depth is an important part of the gas calculation.
Thank you all for your replies and messages. Please bare with me while I get through everything. I will answer everyone in the order received this afternoon.scblade27 11-20-2017 09:19 AM
The official name was Jenny until circa 1976.Jim Wyatt 11-20-2017 09:05 AM
I will take the small Dive Rite reel.
Probably for the best.
And its Jenny springs.
One is a Newfie spelling.Kelly Jessop 11-20-2017 08:40 AM


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The major multiples opened 291 convenience stores in the past year and BWS sales in this channel are up 6.1% in volume and 9.1% in value (IRI, year to March 1).
CAMRA took a swipe at the grocers for turning 208 pubs into c-stores since 2012, but with a dozen closing per week the major retailers are fighting to snap them up.
In total New River, which bought 202 pubs from Marston's in November 2013, is developing almost 200,000 sq ft for c-stores, ranging from 3,000 sq ft to 4,500 sq ft.
The leases run for 15 years.
New River still has 148 former pubs to play around with and said: "The remaining part of the portfolio will be conventional conversions from public house use to C-Stores, or redeveloped as standalone convenience retail stores.
"New River will undertake all planning, development and contract requirements to deliver the end product to The Co-operative Group. It is expected that the majority of the completed assets will be delivered within two years."


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Remington Keratin Therapy Hot Brush
$29.99 for this top grooming brand!
45mm barrel creates volume and waves | Speedy heat up
Curl release | Automatic safety shut off | Salon swivel cord
For luxurious and eye-catching hair, you can't go past this beauty from Remington! Packed with intuitive features and high-quality design - this is your new go-to accessory!
- Remington grooming
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- Variable heat up to 180 degrees celsius
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- Curl release
- Automatic safety shut off
- Automatic worldwide voltage
- Salon swivel cord
- 2 Year Manufacturer Warranty
Customer Reviews
5 Star
4 Star
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2 Star
1 Star


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A former Knox County Schools custodian has been sentenced to six years after pleading guilty to soliciting minors to send him nude photos.
Dustin Lee Dotson pleaded guilty to three counts of solicitation of a minor to engage in certain sexual conduct, a class C felony, in Sept. 2016.
Dotson was a custodian at Inskip Elementary School when he was arrested in June 2016 for asking a 13-year-old girl to send him nude photos. He was fired by the school district soon after his arrest.
After his initial arrest, Knoxville police said a grandmother contacted the department's Major Crimes Unit and said her granddaughter and one of her granddaughter's friends had been by Dotson to send him photos as well. The juveniles were 11 and 12 years old.
Dotson was sentenced Friday by Judge Steve Sword to one year of split confinement and five years probation. Once Dotson is released from jail, he will have to register with the sex offender registry.