IP Library Granted Patent US 11,281,675
Granted Patent B2
US 11,281,675 · App. 16/720,416 · Granted Mar 22, 2022

Method for determining user behavior preference, and method and device for presenting recommendation information

Inventor: Renen Sun (Zhejiang, CN)
Assignee: Advanced New Technologies Co., Ltd.
G06F16/2457G06F16/2379G06F16/248G06F16/35G06F16/9535
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Quick Facts
Patent No.
US 11,281,675
App. No.
16/720,416
Granted
Mar 22, 2022
Kind
B2
Abstract

Recommendation information is associated with an information classification label by a server of an online interaction platform, and a correspondence between the recommendation information and the information classification label is stored in a feature label database. The recommendation information associated with the information classification label is delivered to a user. Upon triggering of the recommendation information by a user, the information classification label associated with the recommendation information and an unique identifier associated with the user are obtained. By using the unique identifier, a user feature database is queried to determine whether a correspondence between the information classification label and the unique identifier has been established. If it is determining that the correspondence is not established, the correspondence between the information classification label and the unique identifier is established in the user feature database.

Claims (63)

1. A computer-implemented method, comprising:

associating, by a server of an online interaction platform, recommendation information with an information classification label, wherein a correspondence between the recommendation information and the information classification label is stored in a feature label database;

delivering the recommendation information associated with the information classification label to a user;

upon triggering of the recommendation information by the user, obtaining the information classification label associated with the recommendation information and an unique identifier associated with the user;

querying, by using the unique identifier, a user feature database to determine whether a correspondence between the information classification label and the unique identifier has been established;

in response to determining that the correspondence between the information classification label and the unique identifier is not established, establishing and storing the correspondence between the information classification label and the unique identifier in the user feature database;

receiving a recommendation request;

identifying a set of information classification labels for which the correspondence between the information classification label and the unique identifier has been established in the user feature database;

generating a sorted order of the set of information classification labels based on a combination of registration information provided by the user and, for each information classification label in the sorted order of the set of information classification labels, a frequency with which the user has triggered recommendation information associated with the information classification label;

selecting, from the sorted order of the set of information classification labels and based on the sorted order, a group of information classification labels;

selecting recommendation information to provide to the user based on the group of information classification labels; and

providing the selected recommendation information to a user device of the user.

2. The computer-implemented method of claim 1 , wherein associating the recommendation information with the information classification label comprises:

determining the correspondence between the recommendation information and the information classification label, wherein the information classification label reflects a classification category of the recommendation information; and

associating the recommendation information and the information classification label based on the determined correspondence.

3. The computer-implemented method of claim 1 , wherein associating the recommendation information with the information classification label comprises:

inserting data associated with the information classification label corresponding to the recommendation information in data associated with the recommendation information; or

inserting, the information classification label corresponding to the recommendation information into a page displaying the recommendation information.

4. The computer-implemented method of claim 1 , wherein the online interaction platform is configured to deliver the recommendation information to the user, and wherein the user triggers the recommendation information by logging into the online interaction platform using a login account.

5. The computer-implemented method of claim 4 , wherein the user triggers different recommendation information that is associated with a plurality of information classification labels.

6. The computer-implemented method of claim 1 , wherein generating the sorted order of the set of information classification labels comprises positioning a particular information classification label in the sorted order based on a match between the particular information classification label and the registration information.

7. A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

associating, by a server of an online interaction platform, recommendation information with an information classification label, wherein a correspondence between the recommendation information and the information classification label is stored in a feature label database;

delivering the recommendation information associated with the information classification label to a user;

upon triggering of the recommendation information by the user, obtaining the information classification label associated with the recommendation information and an unique identifier associated with the user;

querying, by using the unique identifier, a user feature database to determine whether a correspondence between the information classification label and the unique identifier has been established;

in response to determining that the correspondence between the information classification label and the unique identifier is not established, establishing and storing the correspondence between the information classification label and the unique identifier in the user feature database;

receiving a recommendation request;

identifying a set of information classification labels for which the correspondence between the information classification label and the unique identifier has been established in the user feature database;

generating a sorted order of the set of information classification labels based on a combination of registration information provided by the user and, for each information classification label in the sorted order of the set of information classification labels, a frequency with which the user has triggered recommendation information associated with the information classification label;

selecting, from the sorted order of the set of information classification labels and based on the sorted order, a group of information classification labels;

selecting recommendation information to provide to the user based on the group of information classification labels; and

providing the selected recommendation information to a user device of the user.

8. The non-transitory, computer-readable medium of claim 7 , wherein associating the recommendation information with the information classification label comprises:

determining the correspondence between the recommendation information and the information classification label, wherein the information classification label is used to reflect a classification category of the recommendation information; and

associating the recommendation information and the information classification label based on the determined correspondence.

9. The non-transitory, computer-readable medium of claim 7 , wherein associating the recommendation information with the information classification label comprises:

inserting data associated with the information classification label corresponding to the recommendation information in data associated with the recommendation information; or

inserting, the information classification label corresponding to the recommendation information into a page displaying the recommendation information.

10. The non-transitory, computer-readable medium of claim 7 , wherein the online interaction platform is configured to deliver the recommendation information to the user, and wherein the user triggers the recommendation information by logging into the online interaction platform using a login account.

11. The non-transitory, computer-readable medium of claim 10 , wherein the user triggers different recommendation information that is associated with a plurality of information classification labels.

12. A computer-implemented system, comprising:

one or more computers; and

one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising:

associating, by a server of an online interaction platform, recommendation information with an information classification label, wherein a correspondence between the recommendation information and the information classification label is stored in a feature label database;

delivering the recommendation information associated with the information classification label to a user;

upon triggering of the recommendation information by the user, obtaining the information classification label associated with the recommendation information and an unique identifier associated with the user;

querying, by using the unique identifier, a user feature database to determine whether a correspondence between the information classification label and the unique identifier has been established;

in response to determining that the correspondence between the information classification label and the unique identifier is not established, establishing and storing the correspondence between the information classification label and the unique identifier in the user feature database;

receiving a recommendation request;

identifying a set of information classification labels for which the correspondence between the information classification label and the unique identifier has been established in the user feature database;

generating a sorted order of the set of information classification labels based on a combination of registration information provided by the user and, for each information classification label in the sorted order of the set of information classification labels, a frequency with which the user has triggered recommendation information associated with the information classification label;

selecting, from the sorted order of the set of information classification labels and based on the sorted order, a group of information classification labels;

selecting recommendation information to provide to the user based on the group of information classification labels; and

providing the selected recommendation information to a user device of the user.

13. The computer-implemented system of claim 12 , wherein associating the recommendation information with the information classification label comprises:

determining the correspondence between the recommendation information and the information classification label, wherein the information classification label is used to reflect a classification category of the recommendation information; and

associating the recommendation information and the information classification label based on the determined correspondence.

14. The computer-implemented system of claim 12 , wherein associating the recommendation information with the information classification label comprises:

inserting data associated with the information classification label corresponding to the recommendation information in data associated with the recommendation information; or

inserting, the information classification label corresponding to the recommendation information into a page displaying the recommendation information.

15. The computer-implemented system of claim 12 , wherein the online interaction platform is configured to deliver the recommendation information to the user, and wherein the user triggers the recommendation information by logging into the online interaction platform using a login account.

16. The computer-implemented system of claim 15 , wherein the user triggers different recommendation information that is associated with a plurality of information classification labels.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 10, 2020
From: ADVANTAGEOUS NEW TECHNOLOGIES CO., LTD.
To: ADVANCED NEW TECHNOLOGIES CO., LTD.
Reel/Frame 053754/0625 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 31, 2020
From: ALIBABA GROUP HOLDING LIMITED
To: ADVANTAGEOUS NEW TECHNOLOGIES CO., LTD.
Reel/Frame 053743/0464 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 23, 2020
From: SUN, RENEN
To: ALIBABA GROUP HOLDING LIMITED
Reel/Frame 051689/0450 →