Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An online system provides a third party system with the trend in the total monetary value over time for groups of users that meet specific targeting criteria provided by a third party system. The target groups of online system users are divided further into segments according to demographics within the group and their respective base values are observed over an observation time period. Trend values for each segment are formulated based on changes in the respective base values over time. These trend values are weighed according to the number of online system users comprising each segment. More users in a segment results in a larger weight placed on the trend value associated with that segment; fewer users results in a smaller weight. The final value associated with the entire target group of users derives from combining the trend values for each segment within the target group.