Abstract:
Method, system, and programs for mapping data. Information related to users and their interests is obtained by a first application from a second application. An interest space is determined based on one or more sources of information, each of which provides a plurality of concepts. A data structure is created with respect to the interest space, where the data structure has a plurality of attributes each of the attributes corresponds to a concept in the interest space. One or more interests for each of the users based on information obtained from the second application. Each user interest corresponds to an attribute in the structure. A user profile is generated for each user by mapping the interests of the user to the corresponding attributes in the structure.
Abstract:
Method, system, and programs for mapping data. Information related to users and their interests is obtained by a first application from a second application. An interest space is determined based on one or more sources of information, each of which provides a plurality of concepts. A data structure is created with respect to the interest space, where the data structure has a plurality of attributes each of the attributes corresponds to a concept in the interest space. One or more interests for each of the users based on information obtained from the second application. Each user interest corresponds to an attribute in the structure. A user profile is generated for each user by mapping the interests of the user to the corresponding attributes in the structure.
Abstract:
An online article is enhanced by displaying, in association with the article, supplemental content that includes entities that are extracted from the article and/or entities that are related to entities that are extracted from the article. The supplemental content further includes information about each of the entities. The information about an entity may be obtained by searching for the entity in one or more searchable repositories of data. For example, the supplemental content may include, for each entity, video, image, web, and/or news search results. The supplemental content may further include information such as stock quotes, abstracts, maps, scores, and so on. The entities are selected using a variety of analysis and ranking techniques based on contextual factors such as user-specific information, time-sensitive popularity trends, grammatical features, search result quality, and so on. The entities may further be selected for purposes such as generating ad-based revenue.
Abstract:
An online article is enhanced by displaying, in association with the article, supplemental content that includes entities that are extracted from the article and/or entities that are related to entities that are extracted from the article. The supplemental content further includes information about each of the entities. The information about an entity may be obtained by searching for the entity in one or more searchable repositories of data. For example, the supplemental content may include, for each entity, video, image, web, and/or news search results. The supplemental content may further include information such as stock quotes, abstracts, maps, scores, and so on. The entities are selected using a variety of analyses and ranking techniques based on contextual factors such as user-specific information, time-sensitive popularity trends, grammatical features, search result quality, and so on. The entities may further be selected for purposes such as generating ad-based revenue.