METHODS AND SYSTEMS TO RECOMMEND AN ITEM

• US 20090182642A1
• Filed: 07/08/2008
• Published: 07/16/2009
• Est. Priority Date: 01/14/2008
• Status: Abandoned Application

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Sundaresan, Neelakantan
• Application Number:
  US12/169,553
• Publication Number:
  US 20090182642A1
• Time in Patent Office: Days
• US Class Current: 705/26
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0281 Customer communication at a business location, e.g. providing product or service information, consulting
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]

Abstract

Methods and Systems system for recommending an item. The system comprises at least one machine including a receiving module and a recommending module. The receiving module receives an event for an activity related to a first item. Next, the recommending module analyzes recommendation information to identify a first measure of association between the first item and a second item. The recommending module further analyzes recommendation information to identify a second measure of association between the second item and a third item. Finally, the recommendation module communicates a recommendation of the third item responsive to receipt of the event for the activity related to the first item.

Claims

1. A method for recommending an item, the method comprising:

receiving an event for an activity related to a first item;

analyzing recommendation information to identify a first measure of association between the first item and a second item;

analyzing recommendation information to identify a second measure of association between the second item and a third item; and

communicating a recommendation of the third item responsive to receiving the event for the activity related to the first item.

2. The method of claim 1, wherein the activity is selected from group of activities including a bid for the first item, a search request that is used to generate search results that includes the first item, a request to purchase the first item, and a browse request that is used to generate search results that includes the first item.

3. The method of claim 1, further including:

identifying the event is received from a first user;

storing the event in association with the first user;

retrieving a stored event previously received from the first user, the stored event associated with the second item;

identifying the event and the stored event are for updating recommendation information based on a predetermined criterion; and

updating the recommendation information for a first and second item-pair that includes the first item and the second item.

4. The method of claim 1, wherein the identifying the association between the first item and the second item includes identifying a level of association between the first item and the second item based on a first predetermined criterion.

5. The method of claim 1, further including:

analyzing recommendation information to identify a third measure of association between the second item and a fourth item

communicating a recommendation for the fourth item responsive to the receiving the event associated with the first item.

6. The method of claim 1, wherein the communicating the recommendation for the third item includes communicating a user interface element that enables purchase of the third item for a fixed price.

7. The method of claim 1, wherein the communicating the recommendation for the third item includes communicating a user interface element that enables entry of a bid to purchase the third item in an auction.

8. The method of claim 1, wherein the analyzing recommendation information to identify the first measure of association between the first item and the second item sale includes analyzing bid recommendation information to identify a level of association between the first item and the second item based on a predetermined criterion, wherein the predetermined criterion includes a percentage of bids that are received for the first item that are followed by receipt of a bid for the second item.

9. The method of claim 8, wherein the analyzing the recommendation information to identify the second measure of association between the second item and the third item includes analyzing purchase recommendation information to identify a level of association based on a predetermined criterion, wherein the predetermined criterion includes a percentage of requests that are received to purchase the first item that are followed by requests that are received to purchase the second item.

10. A system for recommending an item, the system comprising:

at least one machine including;

a receiving module to receive an event for an activity related to a first item; and

a recommending module to analyze recommendation information to identify a first measure of association between the first item and a second item, the recommending module to analyze recommendation information to identify a second measure of association between the second item and a third item and to communicate a recommendation of the third item responsive to receipt of the event for the activity related to the first item.

11. The system of claim 10, wherein the activity is selected from group of activities including a bid for the first item, a search request that is used to generate search results that includes the first item, a request to purchase the first item, and a browse request that is used to generate search results that includes the first item.

12. The system of claim 10, further wherein the recommendation module is to identify the event is received from a first user, store the event in association with the first user, retrieve a stored event previously received from the first user, the stored event associated with the second item, the recommendation module to identify the event and the stored event are for an update of recommendation information based on predetermined criteria, the recommendation module to update the recommendation information for a first and second item-pair that includes the first item and the second item.

13. The system of claim 10, wherein the recommendation module is to identify a level of association between the first item and the second item based on a first predetermined criterion.

14. The system of claim 10, wherein the recommendation module is to:

analyze recommendation information to identify a third measure of association between the second item and a fourth item; and

communicate a recommendation for the fourth item responsive to the receipt of the event associated with the first item.

15. The system of claim 10, wherein the recommendation module is to communicate a user interface element that enables a purchase of the third item for a fixed price.

16. The system of claim 10, wherein the recommendation module is to communicate a user interface element that enables an entry of a bid to purchase the third item in an auction.

17. The system of claim 10, wherein the recommendation module is to analyze bid recommendation information to identify a level of association between the first item and the second item based on a predetermined criterion, wherein the predetermined criterion includes a percentage of bids that are received for the first item that are followed by receipt of a bid for the second item.

18. The system of claim 17, the recommendation module is to analyze purchase recommendation information to identify a level of association based on a predetermined criterion, wherein the predetermined criterion between the second item and the third item includes a percentage of requests that are received to purchase the first item that are followed by requests that are received to purchase the second item.

19. A system for recommending an item, the system comprising:

at least one machine including;

a first means for receiving an event for an activity related to a first item; and

a recommending module for analyzing recommendation information to identify a first measure of association between the first item and a second item, the recommending module for analyzing recommendation information to identify a second measure of association between the second item and a third item and for communicating a recommendation of the third item responsive to receipt of the event for the activity related to the first item.

20. A machine-readable medium for storing instructions that, when executed by a machine, cause the machine to:

receive an event for an activity related to a first item;

analyze recommendation information to identify a first measure of association between the first item and a second item;

analyze recommendation information to identify a second measure of association between the second item and a third item; and

communicate a recommendation of the third item responsive to receiving the event for the activity related to the first item.