Video content placement optimization based on behavior and content analysis

Patent metadata

Field	Value
Publication number	US-10863224-B2
Application number	US-201916595137-A
Country	US
Kind code	B2
Filing date	Oct 7, 2019
Priority date	May 23, 2005
Publication date	Dec 8, 2020
Grant date	Dec 8, 2020

Abstract

An ad is placed in a movie, by analyzing inherent characteristics of the movie, analyzing viewed characteristics of the movie, analyzing viewer characteristics of a viewer of the movie, obtaining advertiser preferences for placement of the ad in the movie, determining costs of placing the ad in the movie based on the inherent characteristics of the movie, the viewed characteristics of the movie, the viewer characteristics and the advertiser preferences, and placing the ad in the movie in accordance with the inherent characteristics of the movie, the viewed characteristics of the movie, the viewer characteristics, the advertiser preferences and the determined costs.

First claim

What is claimed is:

1. A method of video content placement optimization based on behavior and content analysis, the method comprising:
analyzing, by a computer, video characteristics of a video, the video characteristics of the video including information in the video;
determining, by the computer, whether the video has been previously viewed;
responsive to an indication that the video has been previously viewed, determining, by the computer, viewed characteristics of the video, the determining the viewed characteristics of the video comprising:
obtaining statistics of the video from play trails that track viewing behavior, each play trail representing a timestamped sequence of actions that a viewer takes in playing the video, the statistics of the video including a number of playback events recorded in the play trails;

determining, by the computer, whether content placement in the video is occurring in real time;
responsive to an indication that the content placement in the video is occurring in real time, determining, by the computer, viewer characteristics of the video, including at least one of demographic information of the viewer, an action of the viewer, or a material previously viewed by the viewer;
retrieving or obtaining, by the computer, content placement preferences that specify a content placement price setting mechanism in view of at least one of a video characteristic, a viewed characteristic, or a viewer characteristic, the content placement price setting mechanism including a content placement rule;
determining, by the computer based on the content placement price setting mechanism, a plurality of prices for placing content at a plurality of places in the video;
determining, by the computer based on the content placement rule, whether placement of the content in the video is manual or automatic;
responsive to the content placement rule specifying that the placement of the content in the video is automatic, automatically placing, by the computer, the content in the video at one of the plurality of places in the video; and
responsive to the content placement rule specifying that the placement of the content in the video is manual, notifying, by the computer, a user for manual placement of the content in the video.

2. The method according to claim 1 , wherein the viewed characteristics of the video comprise at least one of a number of times that the video has been requested, a number of times that a link or deep tag to the video has been sent, a number of deep tags in the video, a number of times that a particular segment of the video was replayed, or a number of times that the video was paused at a particular position.

3. The method according to claim 1 , wherein each play trail is stored in a data structure, the data structure having a head that serves as a first statistical unit, the first statistical unit pointing to a next sequential statistical unit corresponding to a next sequential portion of the video.

4. The method according to claim 1 , wherein the video characteristics comprise at least one of a motion, scene change, face presence, or audio track loudness of the video.

5. The method according to claim 1 , wherein the content comprises a video segment and wherein the content placement preferences further include a preference for a type of videos to be combined or inserted with the video segment.

6. The method according to claim 1 , wherein the content placement preferences further include a preference or requirement specifying whether the content is a static insert or a dynamic insert.

7. The method according to claim 1 , further comprising:
delivering the video with the content to a user device;
collecting viewing statistics from the user device; and
storing the viewing statistics in a database.

8. A system for video content placement optimization based on behavior and content analysis, the system comprising:
a processor;
a non-transitory computer-readable medium; and
stored instructions translatable by the processor for:
analyzing video characteristics of a video, the video characteristics of the video including information in the video;
determining whether the video has been previously viewed;
responsive to an indication that the video has been previously viewed, determining viewed characteristics of the video, the determining the viewed characteristics of the video comprising:
obtaining statistics of the video from play trails that track viewing behavior, each play trail representing a timestamped sequence of actions that a viewer takes in playing the video, the statistics of the video including a number of playback events recorded in the play trails;

determining whether content placement in the video is occurring in real time;
responsive to an indication that the content placement in the video is occurring in real time, determining viewer characteristics of the video, including at least one of demographic information of the viewer, an action of the viewer, or a material previously viewed by the viewer;
retrieving or obtaining content placement preferences that specify a content placement price setting mechanism in view of at least one of a video characteristic, a viewed characteristic, or a viewer characteristic, the content placement price setting mechanism including a content placement rule;
determining, based on the content placement price setting mechanism, a plurality of prices for placing content at a plurality of places in the video;
determining, based on the content placement rule, whether placement of the content in the video is manual or automatic;
responsive to the content placement rule specifying that the placement of the content in the video is automatic, automatically placing the content in the video at one of the plurality of places in the video; and
responsive to the content placement rule specifying that the placement of the content in the video is manual, notifying a user for manual placement of the content in the video.

9. The system of claim 8 , wherein the viewed characteristics of the video comprise at least one of a number of times that the video has been requested, a number of times that a link or deep tag to the video has been sent, a number of deep tags in the video, a number of times that a particular segment of the video was replayed, or a number of times that the video was paused at a particular position.

10. The system of claim 8 , wherein each play trail is stored in a data structure, the data structure having a head that serves as a first statistical unit, the first statistical unit pointing to a next sequential statistical unit corresponding to a next sequential portion of the video.

11. The system of claim 8 , wherein the video characteristics comprise at least one of a motion, scene change, face presence, or audio track loudness of the video.

12. The system of claim 8 , wherein the content comprises a video segment and wherein the content placement preferences further include a preference for a type of videos to be combined or inserted with the video segment.

13. The system of claim 8 , wherein the content placement preferences further include a preference or requirement specifying whether the content is a static insert or a dynamic insert.

14. The system of claim 8 , wherein the stored instructions are further translatable by the processor for:
delivering the video with the content to a user device;
collecting viewing statistics from the user device; and
storing the viewing statistics in a database.

15. A computer program product comprising a non-transitory computer-readable medium storing instructions translatable

Assignees

• Open Text Sa Ulc

Inventors

• Gilley Thomas S
• Hoffert Eric
• Nassar Rabih
• Soukup Paul

Classifications

• H04N21/44224 Primary

  Monitoring of user activity on external systems, e.g. Internet browsing · CPC title

• G06Q30/0241

  Advertisements · CPC title

• H04N7/165

  Centralised control of user terminal (subsequent to an upstream request signal H04N7/17345); Registering at central (by two-way working H04N7/17309) · CPC title

• H04N21/4756

  for rating content, e.g. scoring a recommended movie · CPC title

• H04H60/33

  Arrangements for monitoring the users' behaviour or opinions · CPC title