PROCESSING VIDEO USAGE INFORMATION FOR THE DELIVERY OF ADVERTISING
A system and method is provided for generating summaries of video clips and then utilizing a source of data indicative of the consumption by viewers of those video summaries. In particular, summaries of videos are published and audience data is collected regarding the usage of those summaries, including which summaries are viewed, how they are viewed, the duration of viewing and how often. This usage information may be utilized in a variety of ways. In one embodiment, the usage information is fed into a machine learning algorithm that identifies, updates and optimizes groupings of related videos and scores of significant portions of those videos in order to improve the selection of the summary. In this way the usage information is used to find a summary that better engages the audience. In another embodiment usage information is used to predict popularity of videos. In still another embodiment usage information is used to assist in the display of advertising to users.
1 . A method of selecting advertisements comprising the steps of:
analyzing a video comprising a plurality of frames to detect a plurality of parameters associated with said video;
creating at least one summary of said video, wherein each said summary comprises one or more sequences of frames created based on video frames from said video;
publishing said at least one summary making it available to be viewed by a user;
collecting summary usage information from the consumption of said at least one summary by a user comprising collecting data related to the interaction of the user with the at least one summary;
making a decision regarding an advertisement to present to said user based at least in part upon said summary usage information.
2 . The method of claim 1 wherein said step of making a decision is further based on user behavior comprising user preferences and user information.
3 . The method of claim 2 wherein said user preferences includes information regarding a user's previous interaction with summaries, videos or advertisements.
4 . The method of claim 1 wherein said step of creating at least one summary comprises the steps of:
assigning said video to a group based on said parameters;
computing a score for each of a plurality of sequences of frames of said video using a score function and based on properties of said group;
selecting one or more of said sequences of frames based on said score.
5 . The method of claim 4 wherein:
said step of computing a score comprises ranking said plurality of sequences of frames based on a figure of merit creating an ordered list; and
said step of selecting comprises selecting one or more of said plurality of sequences of frames highest on said ordered list.
6 . The method of claim 4 wherein said step of making a decision is further based on properties of said group that said video is assigned to.
7 . The method of claim 1 further comprising the step of:
collecting video usage information from the consumption of said video; and
wherein said step of making a decision is further based on said video usage information.
8 . The method of claim 1 wherein a machine learning mechanism is used by said step of making a decision.
9 . (canceled)
10 . The method of claim 1 wherein said step of creating at least one summary comprises creating a plurality of summaries and wherein said step of publishing comprises making said plurality of summaries available to be viewed by a user.
11 . The method of claim 1 wherein said step of creating at least one summary comprises creating a plurality of summaries and wherein said step of publishing comprises publishing a different summary to each of a least two different users.
12 . The method of claim 1 wherein said data related to the interaction of the user with the at least one summary comprises one or more items from the set consisting of: a number of seconds a user spends watching a summary, an area within a summary window that is clicked, an area within a summary in which the mouse has been placed, a number of times a user sees a summary, a time of a user mouse click relative to a playback of a summary, a time at which a user does a mouse-out event to stop watching a summary without a click, a number of click-throughs to view an original video, a number of total summary views, a number of clicks without watching a summary, a time spent by a user on a site, and a time spent by a user interacting with summaries.
13 . A non-transitory computer readable medium encoded with codes for directing a processor to execute the method of claim 1 .