METHOD AND APPARATUS FOR IMAGE PROCESSING, PROGRAM, AND RECORDING MEDIUM

• US 20130227600A1
• Filed: 03/29/2013
• Published: 08/29/2013
• Est. Priority Date: 09/08/2008
• Status: Active Grant

• Current Assignee: Sony Corporation (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.)
• Inventors: Kamimaeda, Naoki, Masuda, Hiroyuki, Tsunoda, Tomohiro
• Granted Patent: US 9,179,186 B2
• Time in Patent Office: Days
• US Class Current: 725/14
• CPC Class Codes: G06F 16/532 Query formulation, e.g. graphical querying
• CPC Class Codes: G06F 16/5866 using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
• CPC Class Codes: G06F 16/90324 using system suggestions
• CPC Class Codes: G06F 7/24 Sorting, i.e. extracting data from one or more carriers, rearranging the data in numerical or other ordered sequence, and rerecording the sorted data on the original carrier or on a different carrier or set of carriers sorting methods in generalG06F7/36 takes precedence
• 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 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• 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 21/4668 for recommending content, e.g. movies

Abstract

An information processing apparatus includes a managing unit that manages a scale calculated based on descriptions of an operation performed on a predetermined item and a series to which the item belongs in association with each other, a first extracting unit that extracts items belonging to the same series as top N series, obtained by sorting the scales, from among a plurality of items, a taste managing unit that manages taste of a user, a second extracting unit that calculates the degree of similarity between the taste managed by the taste managing unit and each item to extract items with higher degrees of similarity, and a recommending unit that recommends a predetermined number of items among the items extracted by the first extracting unit and the items extracted by the second extracting unit to the user.

Claims

1-8. -8. (canceled)

9. An information processing apparatus comprising:

a scale managing unit configured to manage a scale calculated based on one or more operations performed by a user on a predetermined item;

a first extracting unit configured to extract a first recommendation list, the first recommendation list including items from a recommendation list based on the scales;

a taste managing unit configured to manage taste of the user;

a second extracting unit configured to calculate the degree of similarity between the managed taste and each item to extract a second recommendation list, the second recommendation list including items with higher degree of similarity; and

one or more item recommending units configured to recommend one or more items among the items in the first recommendation list and the second recommendation list to the user.

10. The apparatus according to claim 9, wherein the scale is calculated by adding values set to respective operations of recording, viewing, and transferring the corresponding item to another apparatus.

11. The apparatus according to claim 9, wherein the scale is attenuated at predetermined intervals.

12. The apparatus according to claim 9, further comprising:

a multiplying unit for calculating a value indicating to what extent viewing in series is recommended and multiplying each of the degrees of similarity of the items, extracted by the second extracting unit, by the calculated value.

13. A computer-implemented method for information processing, comprising the steps of:

managing, using at least one processing unit, a scale calculated based on one or more operations performed by a user on a predetermined item;

extracting a first recommendation list, the first recommendation list including items from a recommendation list based on the scales;

managing taste of the user, the taste being stored in storing means;

calculating the degree of similarity between the managed taste and each item to extract a second recommendation list, the second recommendation list including items with higher degree of similarity; and

recommending one or more items among the items in the first recommendation list and the second recommendation list to the user.

14. The method according to claim 13, wherein the scale is calculated by adding values set to respective operations of recording, viewing, and transferring the corresponding item to another apparatus.

15. The method according to claim 13, wherein the scale is attenuated at predetermined intervals.

16. The method according to claim 13, further comprising:

calculating a value indicating to what extent viewing in series is recommended and multiplying each of the degrees of similarity of the items by the calculated value.

17. A recording medium having stored therein a non-transitory computer-readable program that allows a computer to execute a process comprising the steps of:

managing a scale calculated based on one or more operations performed by a user on a predetermined item;

extracting a first recommendation list, the first recommendation list including items from a recommendation list based on the scales;

managing taste of the user, the taste being stored in storing means;

calculating the degree of similarity between the managed taste and each item to extract a second recommendation list, the second recommendation list including items with higher degree of similarity; and

recommending one or more items among the items in the first recommendation list and the second recommendation list to the user.