Abstract: Video trailers for a video quote may be created and provided to a user. The Internet may be searched to identify documents that likely include references to a video. A reference to the video within an identified document may be detected and determined to be a video quote. The video quote and related information may be extracted from the identified document. A location of the video quote within the video may be determined. A video trailer that includes the video quote may be created based on the location of the video quote. A request for a video trailer that includes a video quote or a partial video quote, specified by the user, may be received from the user. A video trailer that includes the video quote or the partial video quote may be identified and provided to the user.

Abstract: Search results may be yielded based on a search query. A search query inspired by a user may be received. Based on the search query, multiple search results each including links may be determined. The multiple search results may include a first search result that includes a link to a first digital instance that describes or embodies a first content item, and a second search result that includes a link to a second digital instance that describes or embodies a second content item. A perceived popularity may be assessed for each of the first and second content items. The perceived popularity may be a measure of the popularity of the first and second content items, and may be distinct from a popularity of the first and second digital instances. A presentation of the multiple search results may be determined based on the accessed perceived popularity.

Abstract: A search query is resolved prior to being submitted to one or more search engines. The query is resolved such that the query unambiguously corresponds to a category included in a query ontology that relates search queries to query categories. The query may be resolved by supplementing the query with additional information corresponding to the category. For example, the query may be formatted into a canonical form of the query for the category. Alternatively or additionally, the query may be supplemented with one or more keywords that are associated with the category and that represent words or phrases that appear in a high percentage of search results for queries from the category. Resolving the query yields search results that more closely reflect search results desired by a user submitting the query.

Abstract: Video trailers for a video quote may be created and provided to a user. The Internet may be searched to identify documents that likely include references to a video. A reference to the video within an identified document may be detected and determined to be a video quote. The video quote and related information may be extracted from the identified document. A location of the video quote within the video may be determined. A video trailer that includes the video quote may be created based on the location of the video quote. A request for a video trailer that includes a video quote or a partial video quote, specified by the user, may be received from the user. A video trailer that includes the video quote or the partial video quote may be identified and provided to the user.

Abstract: A query phrase may be automatically classified to one or more topics of interest (e.g., categories) to assist in routing the query phrase to one or more appropriate backend databases. A selectional preference query classification technique may be used to classify the query phrase based on a comparison between the query phrase and patterns of query phrases. Additionally, or alternatively, a combination of query classification techniques may be used to classify the query phrase. Topical classification of a query phrase also may be used to assist a search system in delivering auxiliary information to a user who entered the query phrase. Advertisements, for instance, may be tailored based on classification rather than query keywords.

Abstract: Search results may be yielded based on a search query. A search query inspired by a user may be received. Based on the search query, multiple search results each including links may be determined. The multiple search results may include a first search result that includes a link to a first digital instance that describes or embodies a first content item, and a second search result that includes a link to a second digital instance that describes or embodies a second content item. A perceived popularity may be assessed for each of the first and second content items. The perceived popularity may be a measure of the popularity of the first and second content items, and may be distinct from a popularity of the first and second digital instances. A presentation of the multiple search results may be determined based on the accessed perceived popularity.

Abstract: Video trailers for a video quote may be created and provided to a user. The Internet may be searched to identify documents that likely include references to a video. A reference to the video within an identified document may be detected and determined to be a video quote. The video quote and related information may be extracted from the identified document. A location of the video quote within the video may be determined. A video trailer that includes the video quote may be created based on the location of the video quote. A request for a video trailer that includes a video quote or a partial video quote, specified by the user, may be received from the user. A video trailer that includes the video quote or the partial video quote may be identified and provided to the user.

Abstract: Search results may be yielded based on a search query. A search query inspired by a user may be received. Based on the search query, multiple search results each including links may be determined. The multiple search results may include a first search result that includes a link to a first digital instance that describes or embodies a first content item, and a second search result that includes a link to a second digital instance that describes or embodies a second content item. A perceived popularity may be assessed for each of the first and second content items. The perceived popularity may be a measure of the popularity of the first and second content items, and may be distinct from a popularity of the first and second digital instances. A presentation of the multiple search results may be determined based on the accessed perceived popularity.

Abstract: A user is made able to configure a search query to be responsive to temporal factors in order to adjust the search query to more accurately reflect the user's true information need. By adjusting the search query in this way, the user is more likely to receive satisfactory search results.

Abstract: A search query is resolved prior to being submitted to one or more search engines. The query is resolved such that the query unambiguously corresponds to a category included in a query ontology that relates search queries to query categories. The query may be resolved by supplementing the query with additional information corresponding to the category. For example, the query may be formatted into a canonical form of the query for the category. Alternatively or additionally, the query may be supplemented with one or more keywords that are associated with the category and that represent words or phrases that appear in a high percentage of search results for queries from the category. Resolving the query yields search results that more closely reflect search results desired by a user submitting the query.

Abstract: A search query is resolved prior to being submitted to one or more search engines. The query is resolved such that the query unambiguously corresponds to a category included in a query ontology that relates search queries to query categories. The query may be resolved by supplementing the query with additional information corresponding to the category. For example, the query may be formatted into a canonical form of the query for the category. Alternatively or additionally, the query may be supplemented with one or more keywords that are associated with the category and that represent words or phrases that appear in a high percentage of search results for queries from the category. Resolving the query yields search results that more closely reflect search results desired by a user submitting the query.

Abstract: A classification system includes a signature-based duplicate detector and an inductive classifier that share attribute information. To perform the duplicate detection and the classification, the duplicate detector and inductive classifier are first initialized by generating a lexicon of attributes for the duplicate detector and a classification model for the classifier. To develop a classification model, a training set of documents of known class are used by the classifier to determine the attributes of the documents that are most useful in classifying an unknown document. The model is developed from these attributes. Attribute information containing the attributes determined by the classifier is then passed to the duplicate detector and the duplicate detector uses the attribute information to generate the lexicon of attributes.

Abstract: A search query is resolved prior to being submitted to one or more search engines. The query is resolved such that the query unambiguously corresponds to a category included in a query ontology that relates search queries to query categories. The query may be resolved by supplementing the query with additional information corresponding to the category. For example, the query may be formatted into a canonical form of the query for the category. Alternatively or additionally, the query may be supplemented with one or more keywords that are associated with the category and that represent words or phrases that appear in a high percentage of search results for queries from the category. Resolving the query yields search results that more closely reflect search results desired by a user submitting the query.

Abstract: In a single-signature duplicate document system, a secondary set of attributes is used in addition to a primary set of attributes so as to improve the precision of the system. When the projection of a document onto the primary set of attributes is below a threshold, then a secondary set of attributes is used to supplement the primary lexicon so that the projection is above the threshold.

Abstract: Video trailers for a video quote may be created and provided to a user. The Internet may be searched to identify documents that likely include references to a video. A reference to the video within an identified document may be detected and determined to be a video quote. The video quote and related information may be extracted from the identified document. A location of the video quote within the video may be determined. A video trailer that includes the video quote may be created based on the location of the video quote. A request for a video trailer that includes a video quote or a partial video quote, specified by the user, may be received from the user. A video trailer that includes the video quote or the partial video quote may be identified and provided to the user.

Abstract: Movie video trailers for a particular movie quote may be created and provided to a user. The Internet may be searched to identify documents that likely include references to a movie. A reference to the movie within an identified document may be detected and determined to be a movie quote. The movie quote and related information may be extracted from the identified document. A location of the movie quote within the movie may be determined. A movie video trailer that includes the movie quote may be created based on the location of the movie quote. A request for a movie video trailer that includes a movie quote or a partial movie quote, specified by the user, may be received from the user. A movie video trailer that includes the movie quote or the partial movie quote may be identified and provided to the user.

Abstract: A classification system includes a signature-based duplicate detector and an inductive classifier that share attribute information. To perform the duplicate detection and the classification, the duplicate detector and inductive classifier are first initialized by generating a lexicon of attributes for the duplicate detector and a classification model for the classifier. To develop a classification model, a training set of documents of known class are used by the classifier to determine the attributes of the documents that are most useful in classifying an unknown document. The model is developed from these attributes. Attribute information containing the attributes determined by the classifier is then passed to the duplicate detector and the duplicate detector uses the attribute information to generate the lexicon of attributes.

Abstract: A document is compared to the documents in a document collection using a hash algorithm and collection statistics to detect if the document is similar to any of the documents in the document collection.

Abstract: Expert domains for a query category represent domains from which a high percentage of search results for queries associated with the query category are retrieved. The expert domains are identified by establishing a base statistical model that indicates frequencies of appearance for domains in search results retrieved for queries corresponding to multiple categories. In addition, frequencies of domain appearance are determined for search results retrieved for queries associated with a category. Domains that appear more frequently in the search results corresponding to the category are identified as expert domains for the category. A user may be allowed to customize expert domains related to one or more categories by adding or removing expert domains for the category.

Abstract: An e-mail filter is used to classify received e-mails so that some of the classes may be filtered, blocked, or marked. The e-mail filter may include a classifier that can classify an e-mail as belonging to a particular class and an e-mail grouper that can detect substantially similar, but possibly not identical, e-mails. The e-mail grouper determines groups of substantially similar e-mails in an incoming e-mail stream. For each group, the classifier determines whether one or more test e-mails from the group belongs to the particular class. The classifier then designates the class to which the other e-mails in the group belong based on the results for the test e-mails.