Information processor, information processing method and computer program

• US 20050144499A1
• Filed: 11/24/2004
• Published: 06/30/2005
• Est. Priority Date: 12/02/2003
• Status: Active Grant

• Current Assignee: Saturn Licensing LLC (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.)
• Inventors: Narahara, Tatsuya, Fujiwara, Nobuyuki
• Granted Patent: US 8,613,023 B2
• Time in Patent Office: Days
• US Class Current: 714/1
• CPC Class Codes: H04H 60/31 Arrangements for monitoring the use made of the broadcast services
• CPC Class Codes: H04H 60/46 for recognising users' preferences
• CPC Class Codes: H04H 60/66 for using the result on distributors' side
• CPC Class Codes: H04H 60/82 the transmission system being the Internet
• 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 21/44224 Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; 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 21/454 Content or additional data filtering, e.g. blocking advertisements
• CPC Class Codes: H04N 21/466 Learning process for intelligent management, e.g. learning user preferences for recommending movies services using the results of monitoring in broadcast systems H04H60/61
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/4821 using a grid, e.g. sorted out by channel and broadcast time
• CPC Class Codes: H04N 21/4826 using recommendation lists, e.g. of programs or channels sorted out according to their score
• CPC Class Codes: H04N 21/4828 for searching program descriptors retrieval of video data G06F16/739
• 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
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

Disclosed is a content-view supporting system to recommend to a user a clear result of searched contents, based on a group of similar users'"'"' favorite programs, through a user-basis collaborative filtering process. The system selects similar users whose program view history is similar to that of a recommended user, maps the program view history in a collaborative filtering matrix registers, in the collaborative filtering matrix, a virtual user whose program view history includes a group of hit programs obtained based on a search condition served for realizing a predetermined search topic. The system also counts the numbers of reservations or views achieved by each user according to program content based on the program view history, in the collaborative filtering matrix, which counted numbers are set as matching numbers, and outputs a search result representing a recommendation list of the contents arrayed in the descending order of matching number.

Claims

1. An information processor for supporting content processing for a recommended user, based on a view history of each of a plurality of users, the processor comprising:

a user'"'"'s view history counter which counts the view history of each of the plurality of users;

a similar user'"'"'s view history counter which retrieves user information representing a user, as a similar user, whose view history is similar to a view history of the recommended user, and counts the view history of the similar user;

a collaborative filtering processor which registers view history information of the recommended user and view history information of the similar user in a collaborative filtering matrix, in which the view history information is mapped in association with each content per user, thereby executing a collaborative filtering process; and

an information creator which creates content recommendation information to be provided to the recommended user, based on a result of the filtering process.

2. The information processor according to claim 1, wherein:

the collaborative filtering processor counts up a number of times the similar user has viewed or reserved each content based on the view history, in the collaborative filtering matrix, thereby obtaining a matching number for each content; and

the information creator creates the content recommendation information to be provided to the recommended user and representing a recommendation list including contents which are selected in order of matching number.

3. The information processor according to claim 2, wherein the information creator affixes additional information of each content into the recommendation list representing the contents.

4. The information processor according to claim 1, further comprising

a virtual user setting unit which sets a virtual user whose view history represents a group of hit contents obtained based on a search condition for realizing a search topic, into the collaborative filtering matrix.

5. The information processor according to claim 4, wherein the information creator creates the content recommendation information which is sorted in groups of contents, one group of which is hits obtained based on a search condition for realizing a predetermined search topic and another group of which is contents that does not satisfy the search condition.

6. The information processor according to claim 4, further comprising

a condition setting unit which sets a search condition for realizing the search topic.

7. The information processor according to claim 4, wherein

the virtual user setting unit registers at least two virtual users in the collaborative filtering matrix at the same time.

8. The information processor according to claim 7, wherein

the virtual user setting unit sets a virtual recommended user whose view history information is included in the view history of the similar user of the recommended user and has a high matching number.

9. An information processing method of supporting content processing for a recommended user, based on a view history of each of a plurality of users, the method comprising:

a user'"'"'s view history counting step of counting the view history of the plurality of users;

a similar user'"'"'s view history counting step of retrieving user information representing a user, as a similar user, whose view history is similar to a view history of the recommended user, and counting the view history of the similar user;

a collaborative filtering processing step of registering view history information of the recommended user and view history information of the similar user in a collaborative filtering matrix, in which the view history information is mapped in association with each content per user, thereby executing a collaborative filtering process; and

an information creating step of creating content recommendation information to be provided to the recommended user, based on a result of the filtering process.

10. The information processing method according to claim 9, wherein:

the collaborative filtering step includes a step of counting up a number of times the similar user has viewed or reserved each content based on the view history, in the collaborative filtering matrix, thereby obtaining a matching number for each content; and

the information creating step includes a step of creating the content recommendation information to be provided to the recommended user, the content recommendation information representing a recommendation list representing contents which are selected in order of matching number.

11. The information processing method according to claim 10, wherein

the information creating step includes a step of affixing additional information of each content into the recommendation list of the contents.

12. The information processing method according to claim 9, further comprising

a virtual user setting step of setting a virtual user whose view history represents a group of hit contents obtained based on a search condition for realizing a search topic, into the collaborative filtering matrix.

13. The information processing method according to claim 12, wherein

the information creating step includes a step of creating the content recommendation information which is sorted in groups of contents, one group of which is hits obtained based on a search condition for realizing a predetermined search topic and another group of which is contents that does not satisfy the search condition.

14. The information processing method according to claim 12, further comprising

a search condition setting step of setting a search condition for realizing the search topic.

15. The information processing method according to claim 12, wherein

the virtual user setting step includes a step of registering at least two virtual users in the collaborative filtering matrix at the same time.

16. The information processing method according to claim 15, wherein

the virtual user setting step includes a step of setting a virtual recommended user whose view history information is included in the view history of the recommended user and has a high matching number.

17. A computer program in a computer readable form, the program executing, on a computer system, information processing for supporting content processing for a recommended user, based on a view history of each of a plurality of users, the computer program comprising:

a user'"'"'s view history counting step of counting the view history of each of the plurality of users;

a similar user'"'"'s view history counting step of retrieving user information representing a user, as a similar user, whose view history is similar to a view history of the recommended user, and counting the view history of the similar user;

a collaborative filtering processing step of registering view history information of the recommended user and view history information of the similar user in a collaborative filtering matrix, in which the view history information is mapped in association with each content per user, thereby executing a collaborative filtering process; and

an information creating step of creating content recommendation information to be provided to the recommended user, based on a result of the filtering process.