PASSIVELY MONITORING ONLINE VIDEO VIEWING AND VIEWER BEHAVIOR

• US 20170346913A1
• Filed: 08/18/2017
• Published: 11/30/2017
• Est. Priority Date: 09/18/2007
• Status: Active Application

• Current Assignee: Adobe Inc.
• Original Assignee: Adobe Systems Incorporated (Adobe Inc.)
• Inventors: Lopatecki, Jason, Rose, Adam, Hughes, John, Wilson, Brett
• Granted Patent: US 10,270,870 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 15/16 Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs coordinating program control therefor G06F9/52; in regulating and control system G05B
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/44226 on social networks
• CPC Class Codes: H04N 21/6582 Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38

Abstract

Various user behaviors are passively monitored and recorded when a user/viewer interacts with a network video player, e.g. a web video player, while watching an online video clip. For one embodiment, a data collection agent (DCA) is loaded to the player and/or to a web page that displays the video clip. The DCA passively collects detailed viewing and behavior information without requiring any specific input or actions on the part of the user. Indications of user preferences are inferred by user actions leading up to viewing the video, while viewing the video, and just after and still related to viewing the video. The DCA periodically sends this information to a central server where it is stored in a central database and where it is used to determine preference similarities among different users. Recorded user preference information may also be used to rate a video itself.

Claims

1. A computer-implemented method of performing analytics of viewing of video clips comprising:

monitorning, by a video analystics server, videos viewed by client devices;

identifying IP addresses of the client devices having viewed the videos;

maintaining a history file of video identifiers that identify videos that have been viewed during a predefined period of time from each IP address of the IP addresses;

detecting that a video corresponding to one of the video IDs has been viewed a number of times from a given IP address that is above a threshold value within the predefined period of time;

determining that attempts are being performed by browser refreshes or scripting that inflate a view count artificially based on the video having been viewed the number of times from the given IP address that is above the threshold value within the predefined period of time; and

discarding subsequent views of the video at the given IP address that has been viewed the video the number of times from the given IP address that is above the threshold value within the predefined period of time.

2. The computer-implemented method of claim 1, when monitoring videos viewed by client devices comprises:

receiving an HTTP requests from client devices having interacted with one or more of the videos;

extracting metadata from the HTTP requests indicating user actions relative to the videos.

3. The computer-implemented method of claim 2, wherein identifying IP addresses of the client devices having viewed the videos comprises extracting the IP addresses from the HTTP requests.

4. The computer-implemented method of claim 2, further comprising inserting a data collection script into a player or webpage that displays the videos, the data collection script programmed to monitor user activity relative to the videos and send activity data to the video analystics server.

12. The method of claim 2, further comprising inserting a data collection script into a player or webpage that displays the videos, the data colleciton script programmed to monitor user activity relative to the videos and send activity data to the video analystics server.

5. A computer-implemented method of generating a viewer preference scores for videos without explicit user feedback comprising:

determining actions of a viewer relative to a video prior to commencement of the video;

determining actions of the viewer relative to the video during play of the video;

determining actions of the viewer relative to the video after completion of the video;

generating a score for the video based on the determined actions of the viewer relative to the video prior to commencement of the video, during play of the video, and after completion of the video; and

associating the generated score with the video.

6. The computer-implemented method of claim 5, wherein determining actions of the viewer relative to the video during play of the video comprises determining whether the viewer:

adjusts a volume level of the video;

pauses or un-pauses the video;

fast-forwards or rewinds the video;

replays the video or a portion thereof;

views the video for a recorded duration or a percent completion;

views the video in full-screen mode;

adjusts a bit rate for streaming or downloading the video during play of the video;

clicks-through on an overlay image or on the video itself to be taken to a webpage or web site;

spends time viewing certain segments of the video;

or

endures a mid-roll advertisement.

7. The computer-implemented method of claim 5, wherein determining actions of the viewer relative to the video after completion of the video comprises determining whether the viewer:

shares the video;

waits for a time duration between viewing the video and initiating a sharing event;

bookmarks the video for later viewing;

downloads and saves the video for later viewing;

or

subscribes to a channel or feed associated with the video.

8. The computer-implemented method of claim 5, wherein determining actions of the viewer relative to the video prior to commencement of the video comprises determining whether the viewer:

endures a pre-roll advertisement;

accesses the video by authenticating, logging-in, or being incentivized to see the video;

or

adjusts a bit rate for streaming or downloading the video prior to playing the video.

9. The computer-implemented method of claim 5, wherein generating the score for the video based on the determined actions of the viewer relative to the video prior to commencement of the video, during play of the video, and after completion of the video comprises differentially weighting the determined actions of the viewer.

10. The computer-implemented method of claim 5, when determining actions of the viewer relative to the video comprises:

receiving one or more HTTP requests from a client device of the viewer; and

extracting metadata from the one or more HTTP requests indicating actions of the viewer relative to the video.

11. The computer-implemented method of claim 10, further comprising identifying an IP address of the client device by extracting the IP address from the one or more HTTP requests.

13. A non-transitory computer-readable medium comprising instructions thereon, that when executed by one or more processors, cause a computing device to:

determine actions of a viewer relative to a video prior to commencement of the video;

determine actions of the viewer relative to the video during play of the video;

determine actions of the viewer relative to the video after completion of the video; and

send the determined actions of the viewer prior to commencement of the video, during play of the video, and after completion of the video to a video analystics server for generating a score for the video based on the determined actions of the viewer.

14. The non-transitory computer-readable medium of claim 13, wherein the instructions, when executed by the one or more processors, cause the computing device to determine actions of the viewer relative to the video during play of the video by determining whether the viewer:

adjusts a volume level of the video;

pauses or un-pauses the video;

fast-forwards or rewinds the video;

replays the video or a portion thereof;

views the video for a recorded duration or a percent completion;

views the video in full-screen mode;

adjusts a bit rate for streaming or downloading the video during play of the video;

clicks-through on an overlay image or on the video itself to be taken to a webpage or web site;

spends time viewing certain segments of the video;

or

endures a mid-roll advertisement.

15. The non-transitory computer-readable medium of claim 13, wherein the instructions, when executed by the one or more processors, cause the computing device to determine actions of the viewer relative to the video after completion of the video by determining whether the viewer:

shares the video;

waits for a time duration between viewing the video and initiating a sharing event;

bookmarks the video for later viewing;

downloads and saves the video for later viewing;

or

subscribes to a channel or feed associated with the video.

16. The non-transitory computer-readable medium of claim 13, wherein the instructions, when executed by the one or more processors, cause the computing device to determine actions of the viewer relative to the video prior to commencement of the video by determining whether the viewer:

endures a pre-roll advertisement;

accesses the video by authenticating, logging-in, or being incentivized to see the video;

or

adjusts a bit rate for streaming or downloading the video prior to playing the video.

17. The non-transitory computer-readable medium of claim 13, wherein the instructions, when executed by the one or more processors, cause the computing device to send the determined actions of the viewer prior to commencement of the video, during play of the video, and after completion of the video to a video analystics server by generating one or more HTTP requests, embedding the determined actions into metadata of the one or more HTTP requests;

and sending the one or more HTTP requests to the video analystics server.

18. The non-transitory computer-readable medium of claim 17, wherein the instructions, when executed by the one or more processors, cause the computing device to identify an IP address of the client device and embed the IP address into the one or more HTTP requests.

19. The non-transitory computer-readable medium of claim 17, wherein the instructions comprise a data collection script configured to be inserted into a player or webpage that display the video.

20. The non-transitory computer-readable medium of claim 17, wherein the instructions, when executed by the one or more processors, cause the computing device to detect that the has been viewed a number of times from a given IP address that is above a threshold value within a predefined period of time;

determine that attempts are being performed by browser refreshes or scripting that inflate a view count artificially based on the video having been viewed the number of times from the given IP address that is above the threshold value within the predefined period of time; and

discard subsequent views of the video at the given IP address that has been viewed the video the number of times from the given IP address that is above the threshold value within the predefined period of time.