IP Library › Granted Patent US 11,120,491
Granted Patent B2
US 11,120,491 · App. 14/457,963 · Granted Sep 14, 2021

Method, medium, and system for social media based recommendations

Inventors: Valerie Nygaard (Saratoga, CA); Ryan Lindsey Helft (Palo Alto, CA)
Assignee: eBay Inc.
G06Q30/0631G06Q30/0282G06Q50/01
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Quick Facts
Patent No.
US 11,120,491
App. No.
14/457,963
Granted
Sep 14, 2021
Kind
B2
Abstract

A user may request a recommendation for an item from other users. Other users may respond to the request by recommending for or against items. Users may up-vote or down-vote the recommendations or responses of other users. The recommendations of the other users may be used to identify items and provide one or more recommendations to the requesting user. The original question and the responses may form a conversation thread. The recommendations may be inserted into the thread as responses, may be presented alongside the thread, or may be presented at the end of the thread. The recommendations may be based on one or more attributes of the user. The weight of the recommendations provided by other users may vary.

Claims (54)

1. A method, performed by an application server comprising a communication module, a recognition module, and a generation module, the method comprising:

receiving, at the communication module via a user interface element displayed on a device of a user, by one or more processors, a user request from other users for a recommendation of an item;

receiving, at the communication module, location information corresponding to a global positioning system (GPS) location of the user device retrieved from a GPS sensor associated with the user device;

accessing, by the communication module from a data storage, a set of comments provided by one or more other users responding to the request, the set of comments including one or more of opinions, commentary, or postings related to the item;

identifying a user corresponding to each comment, from the one or more other users;

for each identified user, determining a number of previously-provided comments that were followed;

parsing, by the recognition module, the set of comments to identify a set of items in a coupled database; and

generating, by the generation module, a recommended item from the set of items identified from the coupled database, the recommended item being selected based on a weight associated with each comment provided by the one or more other users and being based on the number of previously followed comments for the user providing the comment and the GPS location of the user device, the communication module being configured to generate and transmit, to the device of the user, a user interface that presents information about the recommended item to the user, wherein the generating is based on determining that a size of the set of comments exceeds a threshold and also on a momentum of a thread of the set of comments, whereby at least one or more processor cycles are reduced.

2. The method of claim 1 , wherein generating the recommended item is based on an attribute of the user that requested the recommendation.

3. The method of claim 1 , wherein the information about the recommended item is presented alongside the comments provided by the one or more other users.

4. The method of claim 1 , wherein the information about the recommended item is presented inline with the comments provided by the one or more other users.

5. The method of claim 1 , wherein the method further comprises identifying a location of the user and the selecting of the recommended item is further based on the location of the user.

6. The method of claim 1 , wherein the information about the item is one or more of a banner advertisement, a text advertisement, a message, and a pop-up window.

7. The method of claim 1 , wherein the accessing the set of comments provided by the one or more other users responding to the request includes:

accessing a set of comments by the one or more other users; and

for each comment in the set of comments:

determining if a product is mentioned in the comment; and

if a product is mentioned, determining if the comment is positive or negative.

8. The method of claim 1 , wherein:

the method further comprises, for each previously-provided comment that was followed, determining whether the following of the comment resulted in a purchase; and

the number for the user that provided the comment that resulted in a purchase is adjusted based on the determination.

9. The method of claim 1 , wherein:

accessing the set of comments includes detecting, for each comment in the set of comments, a degree to which the comment was agreed with by users; and

generating the recommended item from the set of items is based on the degree to which one or more comments corresponding to the recommended item were agreed with.

10. The method of claim 1 , wherein:

the set of comments are a batch of comments; and

the method further comprises detecting an end of the batch of comments, the detection based on an elapsed time after a last comment exceeding a threshold without a further comment; and

the selecting of the recommended item occurs after the detecting of the end of the batch of comments.

11. The method of claim 10 , further comprising:

detecting a beginning of a second batch of comments, the detection based on a first comment after the transmitting of the information about the recommended item;

detecting an end of the second batch of comments, the detection based on an elapsed time after a second comment exceeding a threshold without an additional comment;

based on the second batch of comments, selecting a second recommended item; and

generating and transmitting, to the device of the user, a second user interface that presents information about the second recommended item to the user.

12. The method of claim 1 , wherein:

the method further comprises identifying a category of the item based on the request of the user; and

the identifying of the recommended item is further based on the category of the item.

13. An application server comprising:

a communication module configured to:

receive, via a user interface element displayed on a device of a user, a user request from other users for a recommendation of an item; and

receive location information corresponding to a global positioning system (GPS) location of the user device retrieved from a GPS sensor associated with the user device;

access, from a storage module, a set of comments provided by one or more other users responding to the request, the set of comments including one or more of opinions, commentary, or postings related to the item;

identify a user corresponding to each comment, from the one or more other users;

for each identified user, determine a number of previously-provided comments that were followed;

a recognition module configured to parse the set of comments to identify a set of items in a coupled database; and

a generation module configured to generate a recommended item from the set of items identified from the coupled database, the recommended item being selected based on a weight associated with each comment provided by the one or more other users and being based on the number of previously followed comments for the user providing the comment and the GPS location of the user device, the communication module being further configured to generate and transmit to the device of the user, a user interface that presents information about the recommended item to the user, the generation module being further configured to generate the recommended item based on determining that a size of the set of comments exceeds a threshold and also on a momentum of a thread of the set of comments, whereby at least one or more processor cycles are reduced.

14. The application server of claim 13 , wherein the generation module generates the recommended item based on an attribute of the user that requested the recommendation.

15. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of an application server comprising a communication module, a recognition module, and a generation module, cause the application server to perform operations comprising:

receiving, at the communication module via a user interface element displayed on a device of a user, a user request from other users for a recommendation of an item;

receiving, at the communication module, location information corresponding to a global positioning system (GPS) location of the user device retrieved from a GPS sensor associated with the user device;

accessing, by the communication module from a data storage, a set of comments provided by one or more other users responding to the request, the set of comments including one or more of opinions, commentary, or postings related to the item;

identifying a user corresponding to each comment, from the one or more other users;

for each identified user, determining a number of previously-provided comments that were followed;

parsing, by the recognition module, the set of comments to identify a set of items in a coupled database; and

generating, by the generation module, a recommended item from the set of items identified from the coupled database, the recommended item being selected based on a weight associated with each comment provided by the one or more other users and being based on the number of previously followed comments for the user providing the comment and the GPS location of the user device, the communication module being configured to generate and transmit, to the device of the user, a user interface that presents information about the recommended item to the user, wherein the generating is based on determining that a size of the set of comments exceeds a threshold and also on a momentum of a thread of the set of comments, whereby at least one or more processor cycles are reduced.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 12, 2014
From: NYGAARD, VALERIE; HELFT, RYAN
To: EBAY INC.
Reel/Frame 033518/0700 →
Continuity (2)
Provisional Application 61881810 · Sep 24, 2013
Related Publication 20150088684A1 · Mar 26, 2015
Cited By (1)
US 12,437,328