1. A method for tagging a latent object with selected tag recommendations, including: receiving an input from a user for tagging the latent object wherein the input includes a user tag preference and wherein the latent object is characterized by a set of predetermined tags representative of an associated set of content features; generating a query using the tag preference for comparing the tag preference to the set of predetermined tags; determining a first annotation relationship between the features and the set of predetermined tags for the object, the relationship being defined by a graph construction representative of an affinity relationship between each predetermined tag and the object content features; determining a second annotation relationship representative of frequency of tagging usage of each of the set of predetermined tags; ranking the first and second annotation relationships based upon a weighted relevance of the predetermined tags and the user tag preference to the object content features using a neighborhood linearization technique to infer edge weights; and suggesting a plurality of suggested tags from the ranking whereby the suggested tags are determined as most likely for annotating the content object.
1. A method for tagging a latent object with selected tag recommendations, including: receiving an input from a user for tagging the latent object wherein the input includes a user tag preference and wherein the latent object is characterized by a set of predetermined tags representative of an associated set of content features; generating a query using the tag preference for comparing the tag preference to the set of predetermined tags; determining a first annotation relationship between the features and the set of predetermined tags for the object, the relationship being defined by a graph construction representative of an affinity relationship between each predetermined tag and the object content features; determining a second annotation relationship representative of frequency of tagging usage of each of the set of predetermined tags; ranking the first and second annotation relationships based upon a weighted relevance of the predetermined tags and the user tag preference to the object content features using a neighborhood linearization technique to infer edge weights; and suggesting a plurality of suggested tags from the ranking whereby the suggested tags are determined as most likely for annotating the content object. 2. The method of claim 1 wherein the determining the first annotation relationship comprises constructing a sparse affinity graph representative of the affinity relationship.