Abstract: A method of detecting associations between items can include identifying a plurality of items represented in a data repository from which to select items to recommend to a target user, each item including one or more attributes. A degree of fit between an item's attributes and other items is calculated. The degree of fit can indicate the relevance of the attributes of one item to the other item. A degree of association between the two items is calculated based at least in part on the calculated degree of fit. The degree of association between the two items can indicate the relatedness of the two items. Based on this degree of association, an association between the items can be stored in a data repository.

Abstract: A recommendation system increases the diversity of item recommendations provided to a target user by using item similarity data to filter an initial recommendation set. In one embodiment, selected items are filtered from the initial recommendation set based on similarity scores that represent degrees of similarity between particular items. The similarity scores may be generated based on an automated comparison of item attributes or content, or based on another measure of item similarity.

Abstract: A content provider system interacts with a network of web sites to provide behavior-based content to users. Operators of the web sites add widgets to selected web pages of their sites. The widgets, when executed on the computing devices of users who view the selected web pages, report user-generated events to the content provider system. The content provider system analyzes the reported events to detect behavioral associations between particular web sites, web pages, products, and/or other types of items. The widgets may also retrieve and display behavior-based content that is based on these item-to-item behavioral associations. For example, when a user views a particular web page, a widget on that page may request and display descriptions of, and links to, other sites or pages that are (a) behaviorally related to the page being viewed or an item represented thereon, and/or (b) behaviorally related to the past browsing activities of the particular user.

Abstract: Sharing of search histories is facilitated with a computer based system and method that allow a searcher to share search results generated without prior authentication of an identity with a search engine. Sharing and collaboration are further facilitated by allowing search history items to be shared with a minimum of additional searcher input. Context for the search history items is provided by associating a search query with an accessed document link without requiring separate tagging of the link by the searcher.

Abstract: A recommendation system increases the diversity of item recommendations provided to a target user by using item similarity data to filter an initial recommendation set. In one embodiment, selected items are filtered from the initial recommendation set based on similarity scores that represent degrees of similarity between particular items. The similarity scores may be generated based on an automated comparison of item attributes or content, or based on another measure of item similarity.

Abstract: A recommendation system increases the diversity of item recommendations provided to a target user by using item similarity data to filter an initial recommendation set. In one embodiment, selected items are filtered from the initial recommendation set based on similarity scores that represent degrees of similarity between particular items. The similarity scores may be generated based on an automated comparison of item attributes or content, or based on another measure of item similarity.

Abstract: Sharing of search histories is facilitated with a computer based system and method that allow a searcher to share search results generated without prior authentication of an identity with a search engine. Sharing and collaboration are further facilitated by allowing search history items to be shared with a minimum of additional searcher input. Context for the search history items is provided by associating a search query with an accessed document link without requiring separate tagging of the link by the searcher.

Abstract: A method of detecting contextual duplicate items can include identifying a plurality of representations of items in a data repository, each item representation including one or more textual attributes. A degree of fit between an item representation's attributes and other items can be calculated. The degree of fit can reflect the relevance of the attributes of one item to the other item. A degree of association between the two item representations can be calculated based at least in part on the calculated degree of fit. The degree of association between the two item representations can reflect the similarity of the two items. The degree of association between the two item representations can be assessed to determine whether the items are contextual duplicates.

Abstract: A method of detecting associations between items can include identifying a plurality of items represented in a data repository from which to select items to recommend to a target user, each item including one or more attributes. A degree of fit between an item's attributes and other items is calculated. The degree of fit can indicate the relevance of the attributes of one item to the other item. A degree of association between the two items is calculated based at least in part on the calculated degree of fit. The degree of association between the two items can indicate the relatedness of the two items. Based on this degree of association, an association between the items can be stored in a data repository.

Abstract: A content provider system interacts with a network of web sites to provide behavior-based content to users. Operators of the web sites add widgets to selected web pages of their sites. The widgets, when executed on the computing devices of users who view the selected web pages, report user-generated events to the content provider system. The content provider system analyses the reported events to detect behavioral associations between particular web sites, web pages, products, and/or other types of items. The widgets may also retrieve and display behavior-based content that is based on these item-to-item behavioral associations. For example, when a user views a particular web page, a widget on that page may request and display descriptions of, and links to, other sites or pages that are (a) behaviorally related to the page being viewed or an item represented thereon, and/or (b) behaviorally related to the past browsing activities of the particular user.

Abstract: A content provider system interacts with a network of web sites to provide behavior-based content to users. Operators of the web sites add widgets to selected web pages of their sites. The widgets, when executed on the computing devices of users who view the selected web pages, report user-generated events to the content provider system. The content provider system analyses the reported events to detect behavioral associations between particular web sites, web pages, products, and/or other types of items. The widgets may also retrieve and display behavior-based content that is based on these item-to-item behavioral associations. For example, when a user views a particular web page, a widget on that page may request and display descriptions of, and links to, other sites or pages that are (a) behaviorally related to the page being viewed or an item represented thereon, and/or (b) behaviorally related to the past browsing activities of the particular user.

Abstract: A content provider system interacts with a network of web sites to provide behavior-based content to users. Operators of the web sites add widgets to selected web pages of their sites. The widgets, when executed on the computing devices of users who view the selected web pages, report user-generated events to the content provider system. The content provider system analyses the reported events to detect behavioral associations between particular web sites, web pages, products, and/or other types of items. The widgets may also retrieve and display behavior-based content that is based on these item-to-item behavioral associations. For example, when a user views a particular web page, a widget on that page may request and display descriptions of, and links to, other sites or pages that are (a) behaviorally related to the page being viewed or an item represented thereon, and/or (b) behaviorally related to the past browsing activities of the particular user.

Abstract: A content provider system interacts with a network of web sites to provide behavior-based content to users. Operators of the web sites add widgets to selected web pages of their sites. The widgets, when executed on the computing devices of users who view the selected web pages, report user-generated events to the content provider system. The content provider system analyses the reported events to detect behavioral associations between particular web sites, web pages, products, and/or other types of items. The widgets may also retrieve and display behavior-based content that is based on these item-to-item behavioral associations. For example, when a user views a particular web page, a widget on that page may request and display descriptions of, and links to, other sites or pages that are (a) behaviorally related to the page being viewed or an item represented thereon, and/or (b) behaviorally related to the past browsing activities of the particular user.

Abstract: A content provider system interacts with a network of web sites to provide behavior-based content to users. Operators of the web sites add widgets to selected web pages of their sites. The widgets, when executed on the computing devices of users who view the selected web pages, report user-generated events to the content provider system. The content provider system analyses the reported events to detect behavioral associations between particular web sites, web pages, products, and/or other types of items. The widgets may also retrieve and display behavior-based content that is based on these item-to-item behavioral associations. For example, when a user views a particular web page, a widget on that page may request and display descriptions of, and links to, other sites or pages that are (a) behaviorally related to the page being viewed or an item represented thereon, and/or (b) behaviorally related to the past browsing activities of the particular user.

Abstract: A recommendation system increases the diversity of item recommendations provided to a target user by using item similarity data to filter an initial recommendation set. In one embodiment, selected items are filtered from the initial recommendation set based on similarity scores that represent degrees of similarity between particular items. The similarity scores may be generated based on an automated comparison of item attributes or content, or based on another measure of item similarity.

Abstract: A method of detecting contextual duplicate items can include identifying a plurality of representations of items in a data repository, each item representation including one or more textual attributes. A degree of fit between an item representation's attributes and other items can be calculated. The degree of fit can reflect the relevance of the attributes of one item to the other item. A degree of association between the two item representations can be calculated based at least in part on the calculated degree of fit. The degree of association between the two item representations can reflect the similarity of the two items. The degree of association between the two item representations can be assessed to determine whether the items are contextual duplicates.

Abstract: A method of detecting associations between items can include identifying a plurality of items represented in a data repository from which to select items to recommend to a target user, each item including one or more attributes. A degree of fit between an item's attributes and other items is calculated. The degree of fit can indicate the relevance of the attributes of one item to the other item. A degree of association between the two items is calculated based at least in part on the calculated degree of fit. The degree of association between the two items can indicate the relatedness of the two items. Based on this degree of association, an association between the items can be stored in a data repository.