Google Inc.

Dimitre Trendafilov

Luciano Sbaiz

Jesse Berent

Effrosyni Kokiopoulou

Fernando Altomare Serboncini

A server computer system identifies activity data for an entity. The activity data for the entity relates to one or more online media items. The server computer system compares the activity data to subscriber data for a channel. The subscriber data includes sets of features for subscribers of the channel. The server computer system determines that the entity is a candidate subscriber for the channel when the activity data corresponds to at least one of the plurality of sets of features.

Identifying candidate subscribers for a channel

A method of predicting interest levels associated with publication and content item combinations is described. Additionally, a server computing device for predicting interest levels associated with publication and content item combinations is described. Further, a computer-readable storage device having processor-executable instructions embodied thereon is described. The processor-executable instructions are for predicting interest levels associated with publication and content item combinations.

Predicting interest levels associated with publication and content item combinations

A system for creating audiences for a shared content publisher, includes a data store comprising a computer readable medium storing a program of instructions for audiences for a shared content publisher; a processor that executes the program of instructions; a data processor to monitor access to an Internet web site by a first set of users for a reference time period; a window extraction module, based on a reference split period, to divide the monitored access into a vector X and a vector Y, wherein vector X is defined by accesses by the first set of users before the reference split period, and vector Y is defined by accesses by the first user after the reference split period; and a data analysis module to create a model based on the vector X and the vector Y, to evaluate the model based on a second set of users accessing content similar to vector X, to create a final model based on the evaluation, and to score a group of users associated with the shared content publisher based on the final model, the data processor monitors accesses by the first user by recording content or shared content identification and additional information items.

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Wollerau, Switzerland

Dimitre Trendafilov