Apparel size service

• US 7,421,306 B2
• Filed: 09/15/2005
• Issued: 09/02/2008
• Est. Priority Date: 09/16/2004
• Status: Active Grant

• Current Assignee: True Fit Corp.
• Original Assignee: Sanghati, LLC
• Inventors: Adiseshan, Kaushie
• Primary Examiner(s): Welch; Gary L.
• Assistant Examiner(s): Durham; Nathan E
• Application Number:
  US11/229,034
• Publication Number:
  US 20060059054A1
• Time in Patent Office: 1,083 Days
• Field of Search: 700/130, 700/131, 700/132, 705/26, 705/27, 703/2, 345/419, 345/420, 345/630, 382/111
• US Class Current: 700/130
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

Embodiments of the present invention provide an apparel size service to provide a customer or user with an apparel size recommendation, for example, by providing information about an appropriate size of apparel for an individual based on comparison information with other apparel, comparison with characteristics of other individuals, and/or comparison with profile and/or history data of the individual.

Claims

1. A computer implemented method, comprising:

receiving by a computing device a request from a user for an apparel size recommendation for a first apparel;

receiving by the computing device from the user one or more characteristics of the user, said one or more characteristics of the user being at least one of style and size data of a second apparel having a suitable fit for the user;

comparing by the computing device said one or more characteristics of the user with corresponding characteristics of one or more additional individuals; and

providing in response to the user by the computing device a size recommendation for the first apparel based at least in part on results of comparing said one or more characteristics of the user with said corresponding characteristics of the one or more additional individuals.

2. The method of claim 1, wherein said providing is further based on profile data of the user.

3. The method of claim 1, wherein said receiving of a request comprises receiving by the computing device a query having style data.

4. The method of claim 1, wherein said providing of a size recommendation comprises providing by the computing device a specific style and size recommendation.

5. The method of claim 1, wherein said providing of a size recommendation comprises providing by the computing device a size recommendation in a range of sizes.

6. The method of claim 1, wherein said providing of a size recommendation comprises providing by the computing device a size recommendation with a likelihood of correctness factor.

7. The method of claim 1, wherein said providing of a size recommendation comprises determining by the computing device an affinity between a first style-size combination and a second style-size combination.

8. The method of claim 7, wherein said determining comprises traversing by the computing device one or more edges of a graph interconnecting first and second nodes of the graph correspondingly representing the first and second style-size combinations.

9. The method of claim 8, wherein the graph comprises a plurality of nodes correspondingly representing style-size combinations of purchases of customers that are similar in age, height and/or weight.

10. The method of claim 7, wherein said providing is further based on purchasing history of the user, and said determining comprises obtaining by the computing device the first style-size combination from the user'"'"'s purchasing history.

11. The method of claim 7, wherein said determining comprises determining by the computing device an affinity between the first style-size combination and a third style-size combination, and an affinity between the second and third style-size combinations.

12. The method of claim 7, wherein the method further comprises storing by the computing device style-size combinations of customer purchases.

13. The method of claim 1, wherein said comparing further comprises comparing the at least one of style and size data of the second apparel having a suitable fit for the user with a corresponding at least one of style and size data of the second apparel having a suitable fit for the one or more additional individuals, and determining a size recommendation for the first apparel for the user by determining a suitable fit of the first apparel for the one or more additional individuals and providing the determined suitable fit as the size recommendation for the first apparel for the user.

14. The method of claim 1, wherein said one or more characteristics of the user further comprise physical characteristics of the user, wherein said comparing further comprises comparing the user with at least one individual from the one or more additional individuals having corresponding physical characteristics, and determining a size recommendation for the first apparel by determining a suitable fit of the first apparel for the at least one individual from the one or more additional individuals having corresponding physical characteristics and providing the determined suitable fit as the size recommendation for the first apparel for the user.

15. The method of claim 14, wherein said physical characteristics include at least one of height, weight, age and gender.

16. A computer implemented method, comprising:

establishing an apparel purchasing history, a profile of a customer, or establishing both and apparel purchasing history and a profile of a customer in a computing device;

initiating a query of the computing device for an apparel size recommendation for an apparel for the customer; and

providing from the computing device a size recommendation for the apparel for the customer based at least in part on said customer apparel purchasing history and/or profile, wherein providing a size recommendation comprises determining by the computing device an affinity between a first style-size combination and a second style-size combination, and wherein said determining comprises traversing by the computing device one or more edges of a graph interconnecting first and second nodes of the graph correspondingly representing the first and second style-size combinations.

17. The method of claim 16, wherein said establishing of a customer apparel purchasing history, when performed, comprises establishing style-size records of apparel purchases of the customer, and said establishing a profile, when performed, comprises establishing a profile containing at least one of the customer'"'"'s height, weight, age and gender.

18. The method of claim 16, wherein providing a size recommendation comprises providing a size recommendation in a range of sizes.

19. The method of claim 16, wherein providing a size recommendation comprises providing a size recommendation with a likelihood of correctness factor.

20. The method of claim 16, wherein said establishing comprises establishing the customer'"'"'s profile, and the graph comprises a plurality of nodes correspondingly representing style-size combinations of purchases of customers that are similar in age, height and/or weight.

21. The method of claim 16, wherein said establishing comprises establishing the customer'"'"'s apparel purchasing history, and said determining comprises obtaining by the computing device the first style-size combination from the customer'"'"'s purchasing history.

22. An apparatus, comprising:

a processor; and

an apparel size service operated by the processor, and adapted to enable the apparatus to receive a request for an apparel size recommendation for a first apparel for a user, to receive from the user one or more characteristics of the user, said one or more characteristics of the user being at least one of style and size data of a second apparel having a suitable fit for the user, to compare said one or more characteristics of the user with corresponding characteristics of one or more additional individuals, and to provide in response for the user a size recommendation for the first apparel based at least in part on results of comparing said one or more characteristics of the user with said corresponding characteristics of the one or more additional individuals.

23. The apparatus of claim 22, wherein said processor and apparel size service are disposed on a server, and said apparatus further comprises a client device coupled to the server, and adapted to facilitate a user in transmitting the request to the server.

24. The apparatus of claim 23, wherein said client device is coupled with said server over a private network, a public network, or both a private network and a public network.

25. The apparatus of claim 22, wherein said processor and apparel size service are disposed on a first server, and said apparatus further comprises an ecommerce service server coupled to the first server and adapted to provider apparel ecommerce service to the user, including apparel size recommendation, using the apparel size service of the first server.

26. The apparatus of claim 25, wherein said apparel size service server and said ecommerce service server are the same server.

27. A computer implemented method, comprising:

obtaining or constructing by a computing device a graph having a plurality of nodes correspondingly representing a plurality of style-size combinations of various apparel, with edges interconnecting the nodes representing style-size combinations with affinity to each other; and

traversing the graph to generate an apparel size recommendation for a user.

28. The method of claim 27, wherein said obtaining or constructing is based at least in part on profile data of the user.

29. The method of claim 27, wherein said traversing is based at least in part on purchasing history of the user.

30. The method of claim 27, wherein said traversing comprises accumulating affinity scores associated with selected edges.

31. A computer implemented method, comprising:

receiving by a computing device a request from a user for an apparel size recommendation for a first apparel;

receiving by the computing device from the user one or more characteristics of the user;

comparing by the computing device said one or more characteristics of the user with corresponding characteristics of one or more additional individuals; and

providing in response to the user by the computing device a size recommendation for the first apparel based at least in part on results of comparing said one or more characteristics of the user with said corresponding characteristics of the one or more additional individuals, wherein providing a size recommendation further comprises determining by the computing device an affinity between a first style-size combination and a second style-size combination.

32. The method of claim 31, wherein said providing is further based on purchasing history of the user, and said determining comprises obtaining by the computing device the first style-size combination from the user'"'"'s purchasing history.

33. The method of claim 31, wherein said determining comprises determining by the computing device an affinity between the first style-size combination and a third style-size combination, and an affinity between the second and third style-size combinations.

34. The method of claim 31, wherein the method further comprises storing by the computing device style-size combinations of customer purchases.