Yahoo! Inc.

Linkedin Corporation

Excalibur Ip, LLC

Microsoft Technology Licensing, LLC

Christina Yip Chung

Long-ji Lin

Hongfeng Yin

Joshua M Koran

Abhinav Gupta

Allen J Blue

George H John

Wei Guan

Richard Frankel

Techniques for identification of a trigger-type leader in a social network are described. According to various embodiments, a specific content item posted by a particular actor of a plurality of actors and interactions by other actors of the plurality of actors with the specific content item are identified. A leadership score associated with the particular actor is then calculated, the leadership score indicating a propensity of the particular actor to stimulate discussion among actors of the online social network service. The particular actor is then classified as an information trigger among the plurality of actors of the online social network service, based on the calculated leadership score.

Identification of a trigger-type leader in a social network

A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Behavioral targeting system

A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, is model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Behavioral targeting system that generates user profiles for target objectives

Techniques for identification of a broker-type leader in a social network based on network topology are described. According to various embodiments, an electronic sociograph is accessed, the electronic sociograph depicting a plurality of actors of an online social network service as nodes in the sociograph, and the sociograph including edges between the nodes representing relationships between the respective actors. Thereafter, a particular node in the sociograph corresponding to an information connector node between at least two distinct groups of the nodes in the sociograph is identified. A particular actor of the plurality of actors associated with the particular node is then classified as an information connector between at least two sub-networks of the actors of the online social network service.

Identification of a broker-type leader in a social network

Techniques for identification of a propagator-type leader in a social network are described. According to various embodiments, a specific content item posted by a particular actor of a plurality of actors and interactions by other actors of the plurality of actors with the specific content item are identified. A leadership score associated with the particular actor is calculated, the leadership score indicating a propensity of the particular actor to spread information among the plurality of actors of the online social network service. The particular actor is then classified as an information propagator among the plurality of actors of the online social network service, based on the calculated leadership score.

Identification of a propagator-type leader in a social network

Incremental update of long-term and short-term user profile scores in a behavioral targeting system

Model for generating user profiles in a behavioral targeting system

Methods and apparatus for a recommendation system based on collaborative filtering is provided. Explicit and implicit ratings of items by network users are used to create a contextual model. The explicit ratings comprise different rating types regarding different item attributes. The implicit ratings comprise different rating types derived from different user events and may include recency, intensity, or frequency ratings. The contextual model may be optimized for a specific objective function, such as click-through-rate or conversion rate. In other embodiments, item information is used to produce a content model where item information for an item is encoded as metadata into a document that represents the item. The contextual or content model is used to recommend one or more items to a current user. The basic unit of the recommendation system may be an item set of two or more items or a particular sequence of two or more items.

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Mountain View, CA, United States of America

Christina Yip Chung