Yahoo! Inc.

Yihong Zhao

Marc Eliot Davis

Xin Li

Alexandra Levich

Yookyung Kim

Tom Chi

Ming Sui

Hongjian Zhao

Lei Guo

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.

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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.

One particular embodiment accesses a plurality of user profiles corresponding to a plurality of users and a plurality of content objects; ranks the users in descending order based on a number of content objects each of the users has contributed to the social network; represents in log space ranks of the users versus in log space numbers of content objects contributed by the users; determines a threshold rank based on an increasing rate of the ranks of the users, a decreasing rate of the numbers of content objects, and a predetermined value in the log space; and identifies from among the users, those users ranked at and above the threshold rank as high-volume content contributors for the social network. The users belong to a social network; and each of the users has contributed at least one of the content objects to the social network.

Identifying top content contributors in online social networks

Growing community of inventors

San Jose, CA, United States of America

Yihong Zhao