INFORMATION-PROCESSING APPARATUS, METHOD, SYSTEM, COMPUTER-READABLE MEDIUM AND METHOD FOR AUTOMATICALLY RECORDING OR RECOMMENDING CONTENT

• US 20150178379A1
• Filed: 02/09/2015
• Published: 06/25/2015
• Est. Priority Date: 12/12/2002
• Status: Active Grant

• Current Assignee: Sony Corporation (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.)
• Inventors: YAMAMOTO, Noriyuki, MIYAZAKI, Mitsuhiro, SAITO, Mari, KOIKE, Hiroyuki
• Granted Patent: US 9,552,413 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3334 Selection or weighting of terms from queries, including natural language queries
• CPC Class Codes: H04L 65/60 Network streaming of media packets
• CPC Class Codes: H04N 21/235 Processing of additional data, e.g. scrambling of additional data or processing content descriptors
• CPC Class Codes: H04N 21/2353 specifically adapted to content descriptors, e.g. coding, compressing or processing of metadata
• CPC Class Codes: H04N 21/26283 for associating distribution time parameters to content, e.g. to generate electronic program guide data
• CPC Class Codes: H04N 21/4325 by playing back content from the storage medium reproduction of recorded television signals H04N5/76; reproduction of recorded television signals H04N9/79
• CPC Class Codes: H04N 21/435 Processing of additional data, e.g. decrypting of additional data, reconstructing software from modules extracted from the transport stream
• CPC Class Codes: H04N 21/44213 Monitoring of end-user related data arrangements for monitoring the users' behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/4661 Deriving a combined profile for a plurality of end-users of the same client, e.g. for family members within a home user profiles in network data switching protocols H04L67/306
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/84 Generation or processing of descriptive data, e.g. content descriptors systems specially adapted for using meta-information in broadcast systems H04H60/73

Abstract

A program vector can represent attributes of a program to be generated. EPG data can be received, and metadata necessary for generation of a program vector PP can be extracted from the EPG data. A morphological analysis can be carried out on contents and title included in the metadata to disassemble the contents and the title into words. Items included in the metadata can be subjected to a vector creation process to generate the program vector PP. An effect vector can be extracted on the basis of a genre of a program associated with the metadata. The extracted effect vector can be associated with the generated program vector PP and the processing can be ended. This can be applied to a distribution server for distributing contents.

Claims

1-18. -18. (canceled)

19. An information processing apparatus, comprising:

a storage that stores content attribute information of content and user preference information of a user; and

circuitry configured to

generate weighted attribute information by weighting each aspect of the content attribute information for the user based on the content attribute information and the user preference information, and

select recommended content based on the weighted attribute information.

20. The information processing apparatus according to claim 19, wherein

the content attribute information includes a content vector that describes aspects of the content, and

the user preference information includes a preference vector that describes aspects of the content that are preferred by a user.

21. The information processing apparatus according to claim 20, wherein the circuitry weights each aspect of the content attribute information by calculating a degree of similarity between the content vector of the content attribute information and the preference vector of the user preference information.

22. The information processing apparatus according to claim 19, wherein

the user preference information includes weighting factors for weighting content attribute information for the user, and

the circuitry weights each aspect of the content attribute information according to the weighting factors.

23. The information processing apparatus according to claim 19, wherein the storage stores recommended content information based on the recommended content selected by the circuitry.

24. The information processing apparatus according to claim 19, wherein the circuitry is further configured to generate the user preference information based on a history of the user.

25. The information processing apparatus according to claim 19, wherein the circuitry is further configured to

receive a content preference input from the user;

modify the weighted attribute information in accordance with the content preference input; and

select the recommended content based on the modified weighted content attribute information.

26. The information processing apparatus according to claim 21, wherein

the content vector includes words,

the preference vector includes weighting factors, the weighting factors being numbers, and

the weighted attribute information includes a corresponding weighting factor from the preference vector for each word from the content vector.

27. The information processing apparatus according to claim 26, wherein the circuitry

calculates a cosine difference between one or more elements of the preference vector with corresponding elements of the content vector, and

calculates the degree of similarity based on the cosine difference.

28. The information processing apparatus according to claim 19, wherein

the content attribute information includes a title of the content, and

the circuitry is further configured to disassemble the title into separate words.

29. An information processing method, comprising:

storing content attribute information of content and user preference information of a user;

generating, by circuitry, weighted attribute information by weighting each aspect of the content attribute information for the user based on the content attribute information and the user preference information; and

selecting, by the circuitry, recommended content based on the weighted attribute information.

30. The information processing method according to claim 29, wherein

the content attribute information includes a content vector that describes aspects of the content, and

the user preference information includes a preference vector that describes aspects of the content that are preferred by a user.

31. The information processing method according to claim 30, wherein the generating of the weighted attribute information includes calculating a degree of similarity between the content vector of the content attribute information and the preference vector of the user preference information.

32. The information processing method according to claim 29, wherein

the user preference information includes weighting factors for weighting content attribute information for the user, and

aspect of the content attribute information is weighted according to the weighting factors.

33. The information processing method according to claim 29, further comprising storing recommended content information based on the selected recommended content.

34. The information processing method according to claim 29, further comprising generating, by the circuitry, the user preference information based on a history of the user.

35. The information processing method according to claim 29, further comprising:

receiving a content preference input from the user; and

modifying, by the circuitry, the weighted attribute information in accordance with the content preference input, wherein

the recommended content is selected based on the modified weighted content attribute information.

36. The information processing method according to claim 31, wherein

the content vector includes words,

the preference vector includes weighting factors, the weighting factors being numbers, and

the weighted attribute information includes a corresponding weighting factor from the preference vector for each word from the content vector.

37. The information processing method according to claim 36, further comprising calculating, by the circuitry, a cosine difference between one or more elements of the preference vector with corresponding elements of the content vector, wherein

the degree of similarity is calculated based on the cosine difference.

38. A non-transitory computer readable medium storing computer executable instructions that, when executed by a computer including a processor, cause the computer to:

store content attribute information of content and user preference information of a user;

generate weighted attribute information by weighting each aspect of the content attribute information for the user based on the content attribute information and the user preference information; and

select recommended content based on the weighted attribute information.