IP Library Granted Patent US 10,762,151
Granted Patent B2
US 10,762,151 · App. 15/695,981 · Granted Sep 1, 2020

Method and device for recommending content to browser of terminal device and method and device for displaying content on browser of terminal device

Inventor: Huijuan Chen (Guangzhou, CN)
Assignee: Guangzhou UCWeb Computer Technology Co., Ltd.
G06F16/9535G06F16/24578G06F16/954G06F16/955G06F16/9537H04L67/02H04L67/18H04L67/22
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Quick Facts
Patent No.
US 10,762,151
App. No.
15/695,981
Granted
Sep 1, 2020
Kind
B2
Abstract

The present disclosure discloses a method and a device for recommending content to a browser of a terminal device and a method and a device for displaying recommended content on a browser of a terminal device. The method for recommending content to a browser of a terminal device includes: recommending content to a browser of a terminal device, where the content includes a first quantity X of popular content of a geographical area to which the terminal device currently belongs, a second quantity Y of content related to a historical user behavior of a user of the browser of the terminal device, and a third quantity Z of content related to a user numerical score of the browser of the terminal device. According to the present disclosure, content matching a browsing interest and habit of a user may be provided, to obtain a relatively high user click-through rate and desirable browsing experience.

Claims (49)

1. A method for recommending content to a browser of a terminal device, comprising:

recommending, to the browser, a first quantity X of popular content of a geographical area to which the terminal device currently belongs, a second quantity Y of content related to a historical user behavior of a user of the browser, and a third quantity Z of content related to a user numerical score of the browser, wherein:

X=CTR 1 /(CTR 1 +CTR 2 +CTR 3 )*B,

Y=CTR 2 /(CTR 1 +CTR 2 +CTR 3 )*B,

Z=CTR 3 /(CTR 1 +CTR 2 +CTR 3 )*B,

CTR 1 is a ratio of a click quantity to a recommendation quantity of the popular content of the user,

CTR 2 is a ratio of a click quantity to a recommendation quantity of the content related to the historical user behavior of the user,

CTR 3 is a ratio of a click quantity to a recommendation quantity of the content related to the user numerical score of the user, and

B is a total display quantity of the recommended content of the terminal device.

2. A device for recommending content to a browser of a terminal device, comprising:

a processor; and

a memory storing computer-readable instructions that, when executed by the processor, cause the processor to recommend, to the browser, a first quantity X of popular content of a geographical area to which the terminal device currently belongs, a second quantity Y of content related to a historical user behavior of a user of the browser, and a third quantity Z of content related to a user numerical score of the browser, wherein:

X=CTR 1 /(CTR 1 +CTR 2 +CTR 3 )*B,

Y=CTR 2 /(CTR 1 +CTR 2 +CTR 3 )*B,

Z=CTR 3 /(CTR 1 +CTR 2 +CTR 3 )*B,

CTR 1 is a ratio of a click quantity to a recommendation quantity of the popular content of the user,

CTR 2 is a ratio of a click quantity to a recommendation quantity of the content related to the historical user behavior of the user,

CTR 3 is a ratio of a click quantity to a recommendation quantity of the content related to the user numerical score of the user, and

B is a total display quantity of the recommended content of the terminal device.

3. A non-transitory storage medium, comprising instructions stored therein, wherein the instructions, when executed by one or more processors, cause the one or more processors to perform a method comprising:

recommending, to the browser, a first quantity X of popular content of a geographical area to which the terminal device currently belongs, a second quantity Y of content related to a historical user behavior of a user of the browser, and a third quantity Z of content related to a user numerical score of the browser, wherein:

X=CTR 1 /(CTR 1 +CTR 2 +CTR 3 )*B,

Y=CTR 2 /(CTR 1 +CTR 2 +CTR 3 )*B,

Z=CTR 3 /(CTR 1 +CTR 2 +CTR 3 )*B,

CTR 1 is a ratio of a click quantity to a recommendation quantity of the popular content of the user,

CTR 2 is a ratio of a click quantity to a recommendation quantity of the content related to the historical user behavior of the user,

CTR 3 is a ratio of a click quantity to a recommendation quantity of the content related to the user numerical score of the user, and

B is a total display quantity of the recommended content of the terminal device.

4. The method according to claim 1 , wherein the popular content is universal popular content of a particular geographical area within a most recent preset time period.

5. The method according to claim 1 , wherein the content related to the historical user behavior is content related to a searching, browsing, or social behavior of the user within a most recent preset time period.

6. The method according to claim 1 , wherein the user numerical score is obtained based on statistical data of the historical user behavior.

7. The method according to claim 1 , wherein

the first quantity, the second quantity Y, and the third quantity are all recommended in an order of quantities of clicks on the related content within a unit time.

8. The method according to claim 1 , further comprising:

collecting geographical position information of the terminal device, and determining the popular content of the geographical area to which the terminal device currently belongs;

collecting a historical user behavior of the user of the browser of the terminal device, performing semantic parsing, and searching for content related to the historical user behavior; and

collecting the historical user behavior of the user of the browser of the terminal device, performing statistical analysis and numerical scoring, and searching, according to the user numerical score, for content matching the user numerical score.

9. The device according to claim 2 , wherein the popular content is universal popular content of a particular geographical area within a most recent preset time period.

10. The device according to claim 2 , wherein the content related to the historical user behavior is content related to a searching, browsing, or social behavior of the user within a most recent preset time period.

11. The device according to claim 2 , wherein the user numerical score is obtained based on statistical data of the historical user behavior.

12. The device according to claim 2 , wherein the instructions, when executed by the processor, further cause the processor to recommend content to a browser of a terminal device all of the first quantity, the second quantity, and the third quantity in an order of quantities of clicks on the related content within a unit time.

13. The device according to claim 2 , wherein the instructions, when executed by the processor, further cause the processor to:

collect geographical position information of the terminal device and determine the popular content of the geographical area to which the terminal device currently belongs;

collect a historical user behavior of the user of the browser of the terminal device, perform semantic parsing, and search for content related to the historical user behavior; and

collect the historical user behavior of the user of the browser of the terminal device, perform statistical analysis and numerical scoring, and search, according to the user numerical score, for content matching the user numerical score.

14. The non-transitory storage medium according to claim 3 , further comprising instructions, when executed by the one or more processors, that cause the one or more processors to perform:

collecting geographical position information of the terminal device, and determining the popular content of the geographical area to which the terminal device currently belongs;

collecting a historical user behavior of the user of the browser of the terminal device, performing semantic parsing, and searching for content related to the historical user behavior; and

collecting the historical user behavior of the user of the browser of the terminal device, performing statistical analysis and numerical scoring, and searching, according to the user numerical score, for content matching the user numerical score.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 29, 2020
From: GUANGZHOU UCWEB COMPUTER TECHNOLOGY CO., LTD.
To: ALIBABA GROUP HOLDING LIMITED
Reel/Frame 053601/0565 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 13, 2017
From: CHEN, HUIJUAN
To: GUANGZHOU UCWEB COMPUTER TECHNOLOGY CO., LTD.
Reel/Frame 043579/0669 →
Priority Claims (1)
CN 2016 1 0812280 · Sep 8, 2016 · national
Continuity (1)
Related Publication 20180068026A1 · Mar 8, 2018