CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is based upon and claims the benefit of priority from the prior Japanese Patent Application No. 2009-160976 filed on Jul. 7, 2009; the entire contents of which are incorporated herein by reference. 
     BACKGROUND 
     1. FIELD 
     The disclosure relates to a mobile communication terminal and a method for recommending a content item. 
     2. DESCRIPTION OF THE RELATED ART 
     It is ordinary known that a mobile communication terminal stores a rule to run a program. If a condition of the mobile communication terminal accords with the rule, the program corresponding to the condition automatically runs. 
     According to a literature, Fumihiko Kato, Norio Toyama, Takashi Hattori &amp; Tatsuya Ogino, working papers for “ 7 th Programming and Application Systems Workshop SPA 2004”, pp. 177-184 (2004), the rule is composed of at least one condition, such as items of a date, a time and a place, and action information. In addition, each condition is defined by at least one condition label. For example, the condition is composed of condition labels of “morning”, “evening” and so on for the time item, and “Pennsylvania Station”, “office” and so on for the place item. 
     The rule is composed of the condition labels and the action information. For example, the rule is defined by “daytime” and “office” as the condition labels, and “display a news program” as the action information. 
     Further, the mobile communication terminal determines whether a condition of the mobile communication terminal accords with each of the condition labels by using sensor data obtained from a sensor. For example, a degree of accord is estimated based on an estimation equation, in such a way that it is estimated that the condition of the mobile communication terminal accords with the condition label in the rule if an output of the estimation equation exceeds a threshold. 
     Then, the condition of the mobile communication terminal satisfies a combination of the condition labels in the rule, a program identified in the rule is automatically run. 
     That is, the mobile communication terminal described above has a condition estimation means for calculating accuracy information which indicates the degree of accord with each of condition labels on the basis of a sensor output, and a recommend rule which sets a combination of the condition labels as a condition and describes a combination of the condition and a content item to be provided. If a combination of condition labels whose accuracy information are greater than a threshold accords with the condition described in the recommend rule, the mobile communication terminal automatically recommends a content item which corresponds to the recommend rule. 
     Incidentally, if a plurality of recommend rules are provided, the above technology has a problem in some cases in that an obtained condition agrees with the plural recommend rules at the same time, and the number of provided content items is greater than the maximum number of recommended content items. As a result, the technology also has a problem in that a content item corresponding to a recommend rule that firmly accords with the condition is covered with a content item that corresponds to a recommend rule of a weaker degree of accord. 
     According to a technology for estimating a condition in which a mobile communication terminal is being put and for recommending, upon the condition according with a specific condition, a content item corresponding to the condition, a result of estimating the condition is treated as an indefinite “accuracy” and a degree to which the accuracy meets the condition is computed and used so that a proper recommendation is somewhat enabled even if the condition is being uncertain. 
     In a case, however, where a condition is treated as the accuracy and a plurality of conditions are specified and specifically described, there is a problem in that a content item is hardly recommended as it is less certain to meet all the conditions. 
     Further, if a plurality of recommend rules are provided, there is a problem in some cases in that an obtained condition accords with the plural recommend rules at the same time, and the number of provided content items is greater than the maximum number of recommended content pieces. As a result, a content item corresponding to a recommend rule that much accords with the condition is covered with content items that correspond to recommend rules of a weaker degree of agreement. 
     SUMMARY 
     Exemplary embodiments of this invention provides a mobile communication terminal that comprises a storage device which stores rule information including at least one pair of condition information and content information for selecting a program to be recommended, wherein the condition information is composed of a plurality of condition labels, a condition estimator which generates condition estimation data indicating accuracy data regarding a condition of the mobile communication terminal for each of a plurality of condition labels based on sensed data, wherein the each condition label is fallen into one of a plurality of condition items, a priority decision section which estimates the rule information and determines priority data for the pair, an estimator which generates an estimation value indicating a summation the accuracy data from the condition estimator and the priority data from the priority decision section, and a selection section which provides a shortcut button to run the program with a display device based on the estimation value and the rule information. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows an exemplary external view of a mobile communication terminal. 
         FIG. 2  shows an example of a schematic configuration of the mobile communication terminal. 
         FIG. 3  shows an example of a condition estimation data. 
         FIG. 4  shows an example of recommendation rules. 
         FIG. 5  shows an example of flowchart of a process for calculating priority data. 
         FIG. 6  shows an example of flowchart of a process for calculating an estimation value. 
         FIG. 7  shows an example of flowchart of a process for selecting a shortcut button. 
     
    
    
     DETAILED DESCRIPTION 
     Exemplary embodiments of the invention are described with reference to the drawings. 
       FIG. 1  shows an example of an external view of a mobile communication terminal  10 .  FIG. 2  shows an example of a system configuration of the mobile communication terminal  10 . For convenience of explanation, only portions directly related to a characteristic of the mobile communication terminal  10  of the embodiment are shown in  FIGS. 1 and 2 . 
     The mobile communication terminal  10  has an input section  100 , a recommendation section  200  and a display section  10 A. 
     The input section  100  receives data from data input devices such as several kinds of sensors, which measure a physical quantity directly or through communication, connected to or integrated in the mobile communication terminal  10 . The data input devices are, e.g., an accelerometer, a GPS device, and a clock device. The mobile communication terminal  10  has these data input devices as means for sensing a condition of the mobile communication terminal  10 . 
     The mobile communication terminal  10  estimates the condition of the mobile communication terminal  10  on the basis of data obtained by the data input devices, chooses a proper content item in accordance with an estimated condition, and indicates the content item on the display section  10 A as, e.g., a short cut button for each of functions of the mobile communication terminal  10 , which will be described in detail later. The mobile communication terminal  10  thereby presents a content item suitable for the condition of the mobile communication terminal  10 . 
     Incidentally, the display section  10 A is, e.g., an LCD display device. 
     The recommendation section  200  has a condition estimator  201 , a recommendation rule DB  202 , a condition decision section  203 , an estimator  204  and a selection section  205 . The condition estimator  201 , the condition decision section  203 , the estimator  204 , and selection section  205  may be realized by a CPU (Central Processing Unit) executing respective programs. 
     The condition estimator  201  estimates a condition of the mobile communication terminal  10  on the basis of data received by the input section  100 , generates condition estimation data  210  and provides the estimator  204  with the condition estimation data  210 . 
     The recommendation rule DB  202  is a database on which recommendation rules  211  are stored. 
     The condition decision section  203  estimates the recommendation rules  211  stored on the recommendation rule DB  202 , and provides the estimator  204  with priority data  212  of the respective recommendation rules  211 . 
     The estimator  204  calculates estimation values  213  of the recommendation rules  211  on the basis of the condition estimation data  210 , the recommendation rules  211  and the priority data  212 , and provides the selection section  205  with the estimation values  213 . 
     The selection section  205  selects a content item to be output and displays a shortcut button  10   a  corresponding to the selected content item on the display section  10 A. Of course, if the selection section  205  determines that there is no content item to be output, no shortcut button  10   a  is displayed on the display section  10 A. Also, if the selection section  205  determines that there are plural content items to be output, shortcut buttons  10   a  are displayed on the display section  10 A. 
     A process performed by the recommendation section  200  will be explained below in detail. 
       FIG. 3  shows an example of the condition estimation data  210  provided by the condition estimator  201 . 
     The condition estimation data  210  generated by the condition estimator  201  includes a “condition label (C 2 )” indicating a condition and an “accuracy label (C 3 ) indicating a degree of accordance between the condition indicated by the condition label and the condition of the mobile communication terminal  10 . Each condition label (C 2 ) is fallen into one of “condition items (C 1 )”. 
     The condition items (C 1 ) may be a time range (C 11 ), a moving condition (C 12 ), a place (C 13 ) and a destination (C 14 ). 
     The condition labels (C 2 ) in the time range (C 11 ) are labels of, e.g., morning, daytime, evening and late night. The condition estimator  201  calculates a time accuracy which shows to what degree a condition indicated by each of the individual condition labels of the time range (C 11 ) accords with present time received by the input section  100 . The present time is measured by the clock device. 
     The condition labels (C 2 ) in the moving condition (C 12 ) are labels of, e.g., a standstill, a walk, a run and a vehicle. The condition estimator  201  calculates a movement accuracy which shows to what degree a condition indicated by each of the individual condition labels of the moving condition (C 12 ) accords with a present condition determined by the input section  100 . The present condition is determined based on acceleration data and position data measured by the accelerometer and the GPS device respectively. 
     The condition labels (C 2 ) in the place (C 13 ) are labels of, e.g., a home, an office and others. The condition estimator  201  calculates place accuracy which shows to what degree a condition indicated by each of the individual condition labels of the place (C 13 ) accords with a present location data received by the input section  100 . The present location data is measured by the GPS device. 
     The condition labels (C 2 ) in the destination (C 14 ) are labels of, e.g., a home, an office and others. The condition estimator  201  calculates destination accuracy which shows to what degree a condition indicated by each of the individual condition labels of the destination (C 14 ) accords with a present place obtained by the input section  100 . The present place is obtained based on position data measured by the GPS device. 
       FIG. 4  shows a table of examples of the recommendation rules  211 . In  FIG. 4 , respective rows of the table show the examples of the recommendation rules  211 . 
     As shown in  FIG. 4 , one of the recommendation rules  211  is composed of an ID (R 1 ), a condition (R 2 ), a content item (R 3 ) and a basic priority (R 4 ). 
     The ID (R 1 ) is an identifier which uniquely identifies one the recommendation rules  211 . 
     The condition (R 2 ) shows conditions each corresponding to one of content items to be recommended in the content item R( 3 ). 
     The content item R( 3 ) shows a content item to be recommended, and its shortcut button  10   a  is displayed on the display section  10 A if the condition (R 2 ) is satisfied. 
     The basic priority (R 4 ) indicates a value for determining a priority order in which the individual content items are recommended in a case where a plurality of the recommendation rules  211  satisfy the conditions at the same time. The value of the basic priority (R 4 ) may be set to dynamically change, e.g., on the basis of a user&#39;s frequency of use. 
     The condition (R 2 ) is defined as a combination of the condition labels (C 2 ) in the condition estimation data  210 . It is supposed that, if the condition labels (C 2 ) classified as the same condition item (C 1 ) are combined, the condition labels have a relationship of “OR” among one another. 
     For instance, the recommendation rule  211  shown in  FIG. 4  for which the ID (R 1 ) is “1” is an example of a recommendation rule that is set for a supposed operation, i.e., “put a start button of a phone call application on the display section upon standing still or walking in the morning”. 
     Thus, the conditions (R 21 ), (R 22 ), (R 23 ) and (R 24 ) corresponding to the “time range (C 11 )”, “moving condition (R 22 ), “place (C 13 )” and “destination (C 14 )” of the state items (C 1 ) are set to “morning”, “standstill or walk”, “wild card (any condition item will do)” and “wild card”, respectively, as the condition (R 2 ). 
     Similarly, the recommendation rule  211  shown in  FIG. 4  for which the ID (R 1 ) is “2” is an example of a recommendation rule that is set for a supposed operation, i.e., “put a start button of an email application on the display section upon standing still or being on a vehicle in the morning or in the evening”. 
     Thus, the conditions (R 21 ), (R 22 ), (R 23 ) and (R 24 ) corresponding to the “time range (C 11 )”, “moving condition (R 22 ), “place (C 13 )” and “destination (C 14 )” of the state items (C 1 ) are set to “morning or evening”, “standstill or walk”, “wild card (any condition item will do)” and “wild card”, respectively, as the condition (R 2 ). 
     Further, the recommendation rule  211  shown in  FIG. 4  for which the ID (R 1 ) is “3” is an example of a recommendation rule that is set for a supposed operation, i.e., “put a switching button to a manner mode on the display section upon being on a vehicle”. 
     Thus, the conditions (R 21 ), (R 22 ), (R 23 ) and (R 24 ) corresponding to the “time range (C 11 )”, “moving condition (R 22 ), “place (C 13 )” and “destination (C 14 )” of the condition items (C 1 ) are set to “wild card”, “vehicle”, “wild card” and “wild card”, respectively, as the condition (R 2 ). 
     Then, the recommendation rule  211  shown in  FIG. 4  for which the ID (R 1 ) is “4” is an example of a recommendation rule that is set for a supposed operation, i.e., “show a news program upon being in the office”. 
     Thus, the conditions (R 21 ), (R 22 ), (R 23 ) and (R 24 ) corresponding to the “time range (C 11 )”, “moving condition (R 22 ), “place (C 13 )” and “destination (C 14 )” of the condition items (C 1 ) are set to “day-time”, “wild card”, “office” and “wild card”, respectively, as the condition (R 2 ). 
     Incidentally, the recommendation rule  211  may be set in a development phase of the mobile communication terminal or by a user&#39;s operation. 
     Incidentally, the condition estimator  203  estimates the recommendation rule  211  read out from the recommendation rule DB  202  with respect to the number of included wild cards from a viewpoint of whether the specific conditions are defined in the recommendation rule  211 , so as to determine a priority of each of the recommendation rules  211 . A process for determining the priority of the recommendation rule  211  by means of the condition estimator  203  will be explained with reference to a flowchart shown in  FIG. 5 . 
     To begin with, the condition estimator  203  sets an initial value of a cumulative wild card value of the recommend rule  211  to be processed to zero (step E 0 ). The method on how to calculate the cumulative wild card value will be explained later. 
     Then, the condition estimator  203  reads the conditions (R 21 , R 22 , R 23  and R 24 ) corresponding to the condition item (C 1 ) from the recommendation rule  211  to be processed in order (step El). 
     Then, the condition decision section  203  calculates a wild card conversion value of the condition corresponding to the condition item that has been read at step E 1  as follows (step E 2 ). 
     The wild card conversion value is made 0 and 1 if the condition corresponding to the condition item (C 1 ) is unique and a wild card, respectively. That is, the wild card conversion value is defined as (the number of ORs of the condition)/((the number of state labels)−1) on the basis of the number of ORs included in the condition. 
     For instance, a case where the condition item (C 1 ) as to the time range (R 21 ) in the conditions (R 2 ) is a wild card is equivalent to a case where the time range (C 11 ) of the state item (C 11 ) is “morning OR daytime OR evening OR late night”. 
     Thus, if the condition of the time range (C 11 ) of the condition item (C 1 ) is a wild card, the wild card conversion value is 3/(4−1)=1. 
     Similarly, if the time range (C 11 ) of the condition item (C 1 ) is “morning OR evening”, the number of ORs is 1 and thus the wild card conversion value is 1/(4−1)=1/3. 
     After calculating the wild card conversion value as described above, the condition decision section  203  adds the calculated wild card conversion value to the cumulative wild card value and updates the cumulative wild card value (step E 3 ). The condition decision section  203  does the above work for all the condition items, and calculates a cumulative wild card value of all the condition items (C 1 ). 
     That is, after finishing the above process (step E 3 ), the condition decision section  203  determines whether the cumulative wild card value of all the condition items has been calculated (step E 4 ). Upon branching off from the step E 4  to “NO”, return to the above (step E 1 ). 
     Meanwhile, upon branching off from the above (step E 4 ) to “YES”, the condition decision section  203  calculates a priority on the basis of the basic priority included in the recommendation rule  211  and the cumulative wild card value as the cumulative wild card value of all the condition items has been calculated (step E 5 ). 
     Concretely, use a discount function f(x) that works in such a way that the output decreases as the input increases at the step E 5 , and calculate the priority as (priority)=(basic priority)×f((cumulative wild card value)). 
     For instance, a function f(x)=(1−a)^x can be an example of the discount function, where a is a constant, 0&lt;a&lt;1 and “^” indicates a power. 
     Incidentally, the cumulative wild card value of the recommendation rule  211  of ID(R 1 )=1 shown in  FIG. 4  is 7/3, and the cumulative wild card value of the recommendation rule  211  of ID(R 1 )=2 shown in  FIG. 4  is 8/3 
     In this case, the output of the discount function is greater for the recommendation rule  211  of ID(R 1 )=1 than for the recommendation rule  211  of ID(R 1 )=2. As described above, the recommendation rule  211  of ID(R 1 )=1 has a higher priority than the recommendation rule  211  of ID(R 1 )=2 even if both the recommendation rules  211  have the same basic priority. 
     Concretely, a difference between the recommendation rule  211  of ID(R 1 )=1 and the recommendation rule  211  of ID(R 1 )=2 is a difference in the time range (R 21 ) and between “morning” and “morning OR evening”. In this case, the former more narrows the condition down and is more specific than the latter. Then, the condition decision section  203  provides the recommendation rule  211  having a more specific condition with the higher priority. 
     A process due to the estimator  204  will be explained below. 
     The estimator  204  calculates the estimation value  213  of the recommendation rule  211  on the basis of the condition estimation data  210 , the recommendation rule  211  and the priority data  212 . A process for calculation the estimation value  213  by means of the estimator  204  will be explained below with reference to a flowchart shown in  FIG. 6 .  FIG. 6  shows a flowchart of the process for calculating the estimation value  213  by means of the estimator  204 . 
     To begin with, the estimator  204  sets an initial value of the estimation value to the priority (step A 0 ). Then, the estimator  204  reads (R 21 , R 22 , R 23  and R 24 ) from the condition (R 2 ) of the recommendation rule  211  corresponding to the condition item (C 1 ) of the condition estimation data  210  in order (step Al). 
     Then, the estimator  204  calculates the “accuracy” regarding the condition item (C 1 ) that has been read at step Al (step A 2 ). 
     Concretely, at step A 2 , the estimator  204  takes the condition label (C 2 ) out from the condition corresponding to the condition item (C 1 ) that has been read, and sums up the accuracy (C 3 ) of the condition estimation data  210  having the same condition label (C 2 ). 
     If the condition is a wild card, the estimator  204  sets 1 to the accuracy at step A 2 . 
     Concretely, at step A 2 , the recommendation rule  211  of ID (R 1 )=1 in the recommend rules  211  shown in  FIG. 4  has the condition of “standstill OR walk” as to the moving state (R 22 ). Thus, if the value of the condition estimation data  210  shown in  FIG. 3  is applied, the accuracy concerning the moving state (R 22 ) is 0.1 (standstill)+0.5 (walk)=0.6. 
     After calculating the accuracy at step A 2 , the estimator  204  integrates the accuracy with the estimation value (step A 3 ). Then, the estimator  204  determines whether the process (step A 1 )−(step A 3 ) has been performed for all the condition items (C 1 ) (step A 4 ). Upon branching off from step A 4  to “NO”, return to step A 1 . 
     Meanwhile, upon branching off from step A 4  to “YES”, the estimator  204  provides the selection section  205  with the value calculated at step A 3  as the estimation value  213  (step A 5 ). 
     A process for selecting an output content item by means of the selection section  205  will be explained below with reference to  FIG. 7 .  FIG. 7  shows a flowchart of the process for selecting an output content item by means of the selection section  205 . 
     To begin with, the selection section  205  determines whether the recommendation rules  211  to be processed exist (step U 1 ). Upon branching off from step U 1  to “NO”, the selection section  205  ends the process. 
     Meanwhile, upon branching off from the (step U 1 ) to “YES”, the selection section  205  reads the recommendation rule  211  of the highest estimation value  213  in the recommendation rules  211  to be processed (step U 2 ). 
     Then, the selection section  205  reads the content item (R 3 ) written in the recommendation rule  211  that has been read at step U 2  (step U 3 ). 
     The selection section  205  determines whether the content item (R 3 ) that has been read at step U 3  and a content item that has been output after the process of the flowchart begins are the same content item (step U 4 ). Upon branching off from step U 4  to “YES”, the process returns to step U 1 . 
     Upon branching off from step U 4  to “NO”, the selection section  205  determines whether the content item is a content item that can be practically output (step U 5 ). If, e.g., the “switching button to a manner mode” content item is a content item to be processed and the mobile communication terminal  10  has already been set to a manner mode, a process for outputting the content item does not make sense. In such a case, the selection section  205  determines that it is a meaningless content item. In this way, upon branching off from step U 5  to “NO”, the process returns to step U 1 . 
     Meanwhile, upon branching off from step U 5  to “YES”, the selection section  205  provides the display section  10 A with the shortcut button  10   a  regarding the recommendable content item and the short-cut button  10   a  is displayed on the display section  10 A (step U 6 ). 
     Then, the selection section  205  determines whether the number of the content items that have been selected exceeds a certain number (step U 7 ). Upon branching off from step U 7  to “YES”, end the process. On the other hand, upon branching off from step U 7  to “NO”, the process returns to step U 1 . 
     According to the embodiment, as described above, the mobile communication terminal  10  recommends a plurality of content items in accordance with a condition of the mobile communication terminal  10  not exceeding the predetermined maximum number of the content items, and further prefers to recommend content items corresponding to a recommendation rule that more firmly accords with the condition. 
     Concretely, e.g., the estimator  204  combines a degree of an agreement between the condition estimation data  210  and the condition (R 2 ) and the accuracy (C 3 ), and treats the combination as an accuracy concerning a condition agreement. Thus, it is enabled to select a content item corresponding to the recommendation rule  211  with a higher degree of the agreement. 
     Further, in order to recommend the content item in accordance with a condition, it is preferable to recommend a content item that more properly accords with a present condition. According to the embodiment, as the estimator  204  estimates a degree of an agreement between the present condition of the mobile communication terminal  10  and the condition in the recommendation rule  211  and recommends a content item on the basis of the estimation, such a recommendation can be implemented. Further, as a priority is set, a priority order among a plurality of recommendation rules is clear. 
     Moreover, it is enabled to prefer to recommend a content item based on a specifically written rule by reducing priority of a recommendation rule of less specific conditions. That is, specificity of the condition can be quantitatively estimated. Concretely, the specificity of the condition is estimated on the basis of the number of “OR relations”. 
     Concretely, e.g., even in a case where the condition estimation data  210  accords with a plurality of the conditions (R 2 ) of the recommendation rules  211  of ID(R 1 )=1 and ID(R 2 )=2 at the same time, such as a case where the condition estimation data  210  indicated “morning, standstill” in the recommendation rule  211  shown in  FIG. 4 , the priority order of the recommendation rule  211  is determined on the basis of the specificity of the condition (the recommendation rule for which the condition is more specifically written is given priority). That is, a content item more suitable for a condition of the mobile communication terminal  10  can be recommended to a user. 
     The present invention has been described above on the basis of the embodiment. The present invention is not limited to the embodiment described above, and it is a matter of course that the embodiment can be variously modified and applied within a scope of the present invention. 
     Further, the embodiment described above includes inventions of various phases, and a plurality of the disclosed portions can be combined so that various inventions can be extracted. In a case, e.g., where the problems to be solved by the invention can be solved and the effect of the invention can be obtained even if some of the whole portions of the embodiment is removed, the configuration without the removed portions can be extracted as an invention.
According to one embodiment, a mobile communication terminal comprises a storage device which stores rule information including at least one pair of condition information and content information, wherein the condition information is composed of a plurality of condition labels, a condition estimator which generates condition estimation data indicating accuracy data regarding a condition of the terminal for each of a plurality of condition labels based on sensed data, wherein the each condition label is fallen into one of a plurality of condition items, a priority decision section which estimates the rule information and determines priority data for the pair, an estimator which generates an estimation value indicating a summation the accuracy data from the condition estimator and the priority data, and a selection section which provides a shortcut button to run a program with a display device based.