Abstract: Techniques for identifying near-duplicates of a media object and associating metadata of the near-duplicates with the media object are described herein. One or more devices implementing the techniques are configured to identify the near duplicates based at least on similarity attributes included in the media object. Metadata is then extracted from the near-duplicates and is associated with the media object as descriptors of the media object to enable discovery of the media object based on the descriptors.

Abstract: A concept network that can be generated in response to a user query. Various embodiments include analysis of structure information, for example, where such information is based at least in part on Universal Resource Locators (URLs) of Web sites or data storage locations. A concept network may be used with a search tool where the search tool searches a plurality of sites (e.g., Web sites, data storage locations, etc.). In such an example, each site location is arranged with a node. Certain ones of the nodes are connected by at least one link. The concept network selects a portion of certain ones of the nodes based on the link, wherein the at least one link is used for content purposes.

Abstract: Method for making a recommendation to a first user in a computing network, including calculating one or more similarity scores between the first user and one or more remaining users in the network, identifying a portion of the remaining users having a highest similarity scores, identifying one or more locations visited by the portion of the remaining users but not by the first user, determining an interest level of the first user in each location, ranking the locations based on the interest levels, and displaying the locations based on the ranking as a first recommendation.

Abstract: A method and system for determining dominance of the media elements of display pages is provided. The dominance system provides a scoring mechanism for scoring the dominance of media elements of display pages based on features of each media element of the display page. To generate the scores for the media elements of the display page, the dominance system first identifies the media elements and then identifies the features of the media elements. The dominance system then scores the identified media elements using the provided scoring mechanism and the identified features.

Abstract: Described is a technology by which forum web pages are processed into clusters for classification purposes, including by determining repetitive regions between pages and associating pages that have similar repetitive regions into a common cluster. Patterns corresponding to the regions are determined, and a feature set based at least in part on those patterns (e.g., pattern frequency) is extracted from the page. The feature set of a page is compared against the feature set of another page to determine similarity therewith, e.g., via a feature space distance computation that is evaluated against a threshold distance.

Abstract: A method and system is provided for determining relevance of an object to a term based on a language model. The relevance system provides records extracted from web pages that relate to the object. To determine the relevance of the object to a term, the relevance system first determines, for each record of the object, a probability of generating that term using a language model of the record of that object. The relevance system then calculates the relevance of the object to the term by combining the probabilities. The relevance system may also weight the probabilities based on the accuracy or reliability of the extracted information for each data source.

Abstract: A method and system for propagating the relevance of labeled documents to a query to unlabeled documents is provided. The propagation system provides training data that includes queries, documents labeled with their relevance to the queries, and unlabeled documents. The propagation system then calculates the similarity between pairs of documents in the training data. The propagation system then propagates the relevance of the labeled documents to similar, but unlabeled, documents. The propagation system may iteratively propagate labels of the documents until the labels converge on a solution. The training data with the propagated relevances can then be used to train a ranking function.

Abstract: A method and system for transmitting an image progressively is provided. The transmission system identifies a first region and a second region of the image. The transmission system also identifies a first resolution and a second resolution. The transmission system then transmits the image by transmitting, in the following order, the first region in the first resolution, the second region in the first resolution, the first region in the second resolution, and the second region in the second resolution. The transmission system may identify the regions based on the likelihood of being the focus of user attention.

Abstract: A method and system for generating a hybrid index for indexing objects based on location and keyword attributes and performing location-based searching is provided. A search system performs a location-based search using a hybrid index that indexes both location and keyword attributes of objects. The search system generates the hybrid index either using the location attribute as the primary index or the keyword attribute as the primary index. When the location attribute is the primary index, the keyword attribute is the secondary index, and vice versa. To generate the hybrid index, the search system identifies the values for the keyword and location attributes of each object. The search system generates the primary index to map each value of a first attribute to a secondary index. The search system thus generates, for each value of the first attribute, a secondary index to map values of a second attribute to objects that have the associated values of the first and second attributes.

Abstract: A large web page is analyzed and partitioned into smaller sub-pages so that a user can navigate the web page on a small form factor device. The user can browse the sub-pages to find and read information in the content of the large web page. The partitioning can be performed at a web server, an edge server, at the small form factor device, or can be distributed across one or more such devices. The analysis leverages design habits of a web page author to extract a representation structure of an authored web page. The extracted representation structure includes high level structure using several markup language tag selection rules and low level structure using visual boundary detection in which visual units of the low level structure are provided by clustering markup language tags. User viewing habits can be learned to display favorite parts of a web page.

Abstract: A method and system for propagating the relevance of labeled documents to a query to unlabeled documents is provided. The propagation system provides training data that includes queries, documents labeled with their relevance to the queries, and unlabeled documents. The propagation system then calculates the similarity between pairs of documents in the training data. The propagation system then propagates the relevance of the labeled documents to similar, but unlabeled, documents. The propagation system may iteratively propagate labels of the documents until the labels converge on a solution. The training data with the propagated relevances can then be used to train a ranking function.

Abstract: A method and system for propagating the relevance of labeled documents to a query to unlabeled documents is provided. The propagation system provides training data that includes queries, documents labeled with their relevance to the queries, and unlabeled documents. The propagation system then calculates the similarity between pairs of documents in the training data. The propagation system then propagates the relevance of the labeled documents to similar, but unlabeled, documents. The propagation system may iteratively propagate labels of the documents until the labels converge on a solution. The training data with the propagated relevances can then be used to train a ranking function.

Abstract: A method and system is provided for determining relevance of an object to a term based on a language model. The relevance system provides records extracted from web pages that relate to the object. To determine the relevance of the object to a term, the relevance system first determines, for each record of the object, a probability of generating that term using a language model of the record of that object. The relevance system then calculates the relevance of the object to the term by combining the probabilities. The relevance system may also weight the probabilities based on the accuracy or reliability of the extracted information for each data source.

Abstract: An object search system generates a hierarchical clustering of objects of a collection based on similarity of the objects. The object search system generates a separate hierarchical clustering of objects for multiple features of the objects. To identify objects similar to a target object, the object search system first generates a feature vector for the target object. For each feature of the feature vector, the object search system uses the hierarchical clustering of objects to identify the cluster of objects that is most “feature similar” to that feature of the target object. The object search system indicates the similarity of each candidate object based on the features for which the candidate object is similar.

Abstract: A method and system for determining dominance of the media elements of display pages is provided. The dominance system provides a scoring mechanism for scoring the dominance of media elements of display pages based on features of each media element of the display page. To generate the scores for the media elements of the display page, the dominance system first identifies the media elements and then identifies the features of the media elements. The dominance system then scores the identified media elements using the provided scoring mechanism and the identified features.

Abstract: Systems and methods for smart media content thumbnail extraction are described. In one aspect program metadata is generated from recorded video content. The program metadata includes one or more key-frames from one or more corresponding shots. An objectively representative key-frame is identified from among the key-frames as a function of shot duration and frequency of appearance of key-frame content across multiple shots. The objectively representative key-frame is an image frame representative of the recorded video content. A thumbnail is created from the objectively representative key-frame.

Abstract: A clustering system generates an original Laplacian matrix representing objects and their relationships. The clustering system initially applies an eigenvalue decomposition solver to the original Laplacian matrix for a number of iterations. The clustering system then identifies the elements of the resultant eigenvector that are stable. The clustering system then aggregates the elements of the original Laplacian matrix corresponding to the identified stable elements and forms a new Laplacian matrix that is a compressed form of the original Laplacian matrix. The clustering system repeats the applying of the eigenvalue decomposition solver and the generating of new compressed Laplacian matrices until the new Laplacian matrix is small enough so that a final solution can be generated in a reasonable amount of time.

Abstract: An object search system generates a hierarchical clustering of objects of a collection based on similarity of the objects. The object search system generates a separate hierarchical clustering of objects for multiple features of the objects. To identify objects similar to a target object, the object search system first generates a feature vector for the target object. For each feature of the feature vector, the object search system uses the hierarchical clustering of objects to identify the cluster of objects that is most “feature similar” to that feature of the target object. The object search system indicates the similarity of each candidate object based on the features for which the candidate object is similar.

Abstract: A method and system for determining relevance of a document having text and images to a text string is provided. A scoring system identifies image text associated with an image of the document. The scoring system calculates an image score indicating relevance of the image text to the text string. The image score may be used in many applications, such as searching, summary generation, and document classification, image search, and image classification.

Abstract: Search results are ranked by applying sub-relevancies within a search result list. This permits search result lists to be further refined into more manageable relevant groupings from a user's perspective. The sub-relevancies or ‘group-by’ parameters are derived from search result attributes. Attribute values from the attributes are employed in a ranking scheme to group the search results based on attribute value relevancy. The grouped search results can then be displayed to users via a search result page. In one instance users can select which attribute value is used to group the search result list. Ranking processes are based on object ranking algorithms that consider each attribute value as an object type. Some instances provide for search result list group condensing based on relevancy of the attribute values as well. A top-k instance can be employed to limit the search results to control the amount of time required for processing groupings.