SYSTEM, APPARATUS, AND METHOD FOR RECOMMENDING ITEMS

• US 20130262478A1
• Filed: 03/15/2013
• Published: 10/03/2013
• Est. Priority Date: 03/30/2012
• Status: Active Grant

• Current Assignee: Sony Corporation (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.)
• Inventors: Kemp, Thomas, Miyahara, Masanori, Kamimaeda, Naoki
• Granted Patent: US 9,298,809 B2
• Time in Patent Office: Days
• US Class Current: 707/748
• CPC Class Codes: G06F 16/3334 Selection or weighting of terms from queries, including natural language queries
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Recommending one or more items among a plurality of items to a first user by generating a weighted data set by applying a weight factor to each of a plurality of user event data sets each derived from a previous user event of a second user of the recommendation system. Each of the user event data sets includes a user identifier of the second user, an item identifier of an item involved in the previous user event, and time information regarding a time of the previous user event. The weight factor is derived from the time information of the corresponding previous user event. One or more recommended items are determined based on an algorithm using the weighted data set.

Claims

1. A method performed by an information processing apparatus for recommending one or more items among a plurality of items to a first user of a recommendation system, the method comprising:

generating, using circuitry of the information processing apparatus, a weighted data set by applying a first weight factor to each of a plurality of user event data sets each derived from a previous user event of a second user of the recommendation system, wherein

each of the user event data sets includes a user identifier of the second user, an item identifier of an item involved in the previous user event, and time information regarding a time of the previous user event, and

the first weight factor is derived from the time information of the previous user event; and

determining, using the processing circuitry, the one or more recommended items based on an algorithm using the weighted data set.

2. The method according to claim 1, further comprising:

deriving, using the circuitry, the first weight factor of the user event data sets from a time difference between a current time and the time of the previous user event of the user event data set.

3. The method according to claim 2, wherein said deriving includes deriving the first weight factor of the user event data sets from an exponential function of the time difference between the current time and the time of the previous user event of the user event data set.

4. The method according to claim 2, wherein the deriving includes deriving the first weight factor of the user event data sets from a linear function of the time difference between the current time and the time of the previous user event of the user event data set.

5. The method according to claim 1, further comprising:

deriving, using the circuitry, the first weight factor of the user event data sets from an order of previous user events of the second user.

6. The method according to claim 1, further comprising:

determining, using the circuitry, similarities between at least one of users of the recommendation system and between items among the plurality of items; and

determining, using the processing circuitry, recommendation values for the one or more items based on the determined similarities and based on the weighted data set.

7. The method according to claim 6, wherein said determining similarities includes determining similarities based on the weighted data set.

8. The method according to claim 1, wherein the user events are purchase events.

9. The method according to claim 1, further comprising:

generating, using the circuitry, a matrix based on the plurality of user event data sets; and

applying, using the circuitry, a second weight factor to one or more elements of the matrix.

10. An information recommendation apparatus comprising:

circuitry configured to

generate a weighted data set by applying a weight factor to each of a plurality of user event data sets, each derived from a previous user event of a second user of the apparatus, wherein

each of the user event data sets includes a user identifier of the second user, an item identifier of an item involved in the previous user event, and time information regarding a time of the previous user event, and

the weight factor is derived from the time information of the previous user event;

determine one or more recommended items based on an algorithm using the weighted data set; and

store the plurality of user event data sets in a memory.

11. The information recommendation apparatus according to claim 10, wherein the circuitry is configured to store the weighted data set in the memory.

12. A non-transitory computer-readable storage medium storing computer-readable instructions that, when executed by a computer of a recommendation apparatus, cause the recommendation apparatus to perform a method comprising:

generating a weighted data set by applying a weight factor to each of a plurality of user event data sets, each derived from a previous user event of a second user of a recommendation system, wherein

each of the user event data sets includes a user identifier of the second user, an item identifier of an item involved in the previous user event, and time information regarding a time of the previous user event, and

the weight factor is derived from the time information of the previous user event; and

determining one or more recommended items based on an algorithm using the weighted data set.