Facebook, Inc.

Jiajin Yu

Spencer Powell

Zhengyong Zhu

Max K Comer

Kevin Wenkai Heh

Rajat Raina

Ashish Gupta

An online system receives a video-presentation request from a third party system. The video-presentation request comprises a video and a target audience specification for the video. The online system selects a plurality of users as the target audience of the video based on the target audience specification. From the target audience, the online system generates a sample subset of users and determines a sampled video reach count for the subset of users. A sample user who, as determined by the online system, would have viewed the view for at least a threshold duration, is included in the sampled video view count. The online system estimates a total video reach count for target audience by extrapolating the sampled video reach count for the subset of users to the target audience. The total video reach count can be used to determine a parameter for presenting the video on an online system.

Computation of video presentation statistics in an online system

In one embodiment, a method includes receiving a search query and identifying one or more n-grams. The method also includes accessing, for each identified n-gram, a time-based distribution that includes a count of actions associated with the n-gram. The actions may have occurred within several time windows, and the time-based distribution may count the actions within each time window. The method may also include determining one or more extrema time windows. The method may also include modifying the search query based on the determined extrema time windows. The method also includes executing the modified search query, ranking identified content objects, and sending search results to a client system. The search results may be displayed in ranked order based on the rankings of the corresponding content objects.

Time-window counters for search results on online social networks

An online system scores campaign audiences based on historical scoring data for similar audiences. A third party system selects a target audience and a day on which the target audience should be exposed to a campaign. The online system generates an availability grid and a score grid to determine a score for the target audience. Values in the availability grid are determined based on the availability of exposure time for the target audience on the specified date. Values in the score grid are based on historical scoring data for the same audience. The online system scores the target audience by interpolating between data points in the score grid based on a selected availability from the availability grid.

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Fremont, CA, United States of America

Jiajin Yu