Recommendations based upon explicit user similarity

Patent metadata

Field	Value
Publication number	US-11836780-B2
Application number	US-202017012316-A
Country	US
Kind code	B2
Filing date	Sep 4, 2020
Priority date	Mar 15, 2013
Publication date	Dec 5, 2023
Grant date	Dec 5, 2023

Abstract

A system and method for providing recommendations to individuals on a social network, in which the recommendations include information indicating the similarity of the individuals to one another, to aid the individuals in judging the degree to which the opinions of the others are applicable to the themselves.

First claim

What is claimed is:

1. A system, wherein the system comprises:
one or more processors configured to:
characterize a first user and a second user based on interaction information for the first user and the second user via a network;
generate a level of similarity of the first user and the second user based on the interaction information;
provide, to the first user, a recommendation of a product or a service based on the interaction information for the first user and the second user and the similarity level;
provide, to the first user, information relating to the second user so that reasons for the similarity can be reviewed by the first user;
present, via a selection of one or more graphical elements of a graphical user interface when the information relating to the second user is presented, a list of categories and their respective similarity levels; and
present, via a selection of one or more graphical elements of the graphical user interface, how one or more of the similarity levels are calculated.

2. The system according to claim 1 , wherein the network comprises an e-commerce system.

3. The system according to claim 1 , wherein the interaction information is based on online social network activities of the first user and the second user via the network.

4. The system according to claim 1 , wherein the interaction information is based on implicit interactions.

5. The system according to claim 1 , wherein the level of similarity of the first user and the second user is generated according to an aggregated similarity level based on user interests and product preferences.

6. The system according to claim 1 , wherein the recommendation provided to the first user are according to a level of similarity of a first attribute weight vector and a second attribute weight vector.

7. The system according to claim 1 , wherein the interaction information is based on one or more of a vote on an online survey, an addition of an item to an online shopping cart, a purchase of one or more items, and an addition of an item to a catalog.

8. The system according to claim 1 , wherein the level of similarity of the first user and the second user is generated according to an aggregated similarity level based on user interests and product preferences.

9. The system according to claim 1 , wherein the level of similarity of the first user and the second user is generated according to the aggregated similarity level using answers to online surveys.

10. The system according to claim 1 , wherein the first user and the second user are characterized according to attributes.

11. The system according to claim 10 , wherein the level of similarity of the first user and the second user is generated according to an adjustment of a plurality of weights for each of the first user and the second user based upon a number of distinct users associated with each attribute.

12. The system according to claim 1 , wherein the list of categories and their respective similarity levels are used to determine whether opinions of the second user are useful to the first user.

13. The system according to claim 1 , wherein the one or more processors are configured to normalize the similarity levels for corresponding categories into different level categories.

14. The system according to claim 13 , wherein the normalized similarity levels comprise two or more different level categories.

15. The system according to claim 13 , wherein the normalized similarity levels comprise three or more different level categories.

16. The system according to claim 1 , wherein a privacy aspect of the second user is maintained.

17. The system according to claim 16 , wherein particular purchases of the second user are not revealed.

18. The system according to claim 1 , wherein the one or more processors are configured to:
express a strength of a relationship between the first user and each of a plurality of attributes as a plurality of weights; and
express a strength of a relationship between the second user and each of a plurality of attributes as a plurality of weights.

19. The system according to claim 18 , wherein the one or more processors are configured to calculate a metric of similarity of the first user and the second user according to the weights of the first user and the weights of the second user.

20. The system according to claim 19 , wherein the one or more processors are configured to express a graphical indication representing the similarity metric.

Assignees

• Transf Sr Brands Llc

Inventors

• Egozi Ofer
• Moran Amit
• Shamir Oren

Classifications

• G06Q10/40

  Business processes related to social networking or social networking services · CPC title

• G06Q10/42

  Determination of affinities or common interests between users · CPC title

• G06Q30/0631 Primary

  Recommending goods or services · CPC title

• G06Q10/10

  Office automation; Time management · CPC title

• G06Q30/02

  Marketing; Price estimation or determination; Fundraising · CPC title