METHOD, APPARATUS AND SYSTEM OF INTELLIGENT NAVIGATION

• US 20170091339A1
• Filed: 12/13/2016
• Published: 03/30/2017
• Est. Priority Date: 06/12/2010
• Status: Active Grant

• Current Assignee: Alibaba Group Holding Ltd.
• Original Assignee: Alibaba Group Holding Ltd.
• Inventors: PAN, Chunxiang
• Granted Patent: US 9,842,170 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/1734 Details of monitoring file system events, e.g. by the use of hooks, filter drivers, logs
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/3325 Reformulation based on results of preceding query
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

The present disclosure describes a method, an apparatus and a system of intelligent navigation. In one embodiment, a method includes: receiving a user inquiry from a client terminal; searching a navigation dictionary based on the user inquiry to obtain a recommendation result corresponding to the user inquiry, the navigation dictionary including an editor recommendation based on user behavior information; and sending the recommendation result to the client terminal. The present disclosure can enhance the accuracy, relevancy, richness and intelligence of the intelligent navigation, and reduce user search time as well as the search loading on the server.

Claims

1. A method implemented by one or more computing devices, the method comprising:

sending a user inquiry to a server from a client device, wherein said user inquiry comprises one or more types of content; and

receiving a recommendation result at the client device responsive to the user inquiry,

wherein the recommendation result corresponds to the user inquiry and comprises types of content, wherein said types of content of the recommendation result are obtained based at least in part on the one or more types of content in the user inquiry, wherein further a navigation dictionary is compiled based upon user behavior information associated with a user of the client device, and the recommendation result is sent to the client device from the server responsive to the user inquiry being located in the navigation dictionary.

2. The method as recited in claim 1, wherein the navigation dictionary is compiled by:

generating reference data based at least in part on statistics obtained from the user behavior information;

compiling the reference data to obtain an editor recommendation corresponding to the user behavior information; and

compiling the editor recommendation into a navigation dictionary.

3. The method as recited in claim 2, wherein the user inquiry comprises a search keyword, and wherein the editor recommendation comprises an index keyword and recommendation content.

4. The method as recited in claim 3, wherein the editor recommendation is searched for in the navigation dictionary based at least in part on search keyword, and the recommendation content is used as the recommendation result.

5. The method as recited in claim 2, wherein the user inquiry further comprise a search keyword, and wherein the editor recommendation comprises an index keyword, a recommendation type, and a recommendation content.

6. The method as recited in claim 5, further comprising;

displaying the recommendation content on a user interface of the client device based at least its part on a format according to the recommendation type.

7. The method as recited in claim 2, further comprising:

sending user feedback information corresponding to the editor recommendation to the server; and

receiving an indication that the editor recommendation is valid based at least in part on the user feedback information.

8. The method as recited in claim 2, further comprising:

sending user feedback information corresponding to the editor recommendation to the server; and

receiving a modified editor recommendation responsive to a determination that the editor recommendation is invalid.

9. The method as recited in claim 2, wherein a user behavior log is generated based at least in part on the user behavior information, wherein the user behavior log comprises a search log, and wherein the reference data comprises a keyword, a search category, and search data.

10. The method as recited in claim 9, wherein compiling the reference data comprises:

when the search data of the reference data is greater than a predetermined threshold, generating the editor recommendation, wherein the editor recommendation comprises an index keyword, an index, category, and recommendation content based at least in part on the reference data, and

wherein the index keyword comprises a keyword of the reference data, wherein the index category comprises a search category of the reference data, and wherein the recommendation content comprises a category, an attribute, or a combination of the category and the attribute corresponding to the search data haying a greatest value in the reference data.

11. The method as recited in claim 2, wherein a user behavior log is generated based at least in part on the user behavior information, wherein, the user behavior log comprises a clicking log, and wherein the reference data comprises a keyword, a search category, and clicking data.

12. The method as recited in claim 11, wherein compiling the reference data comprises:

when the clicking data of the reference data is greater than a predetermined threshold, generating the editor recommendation, wherein the editor recommendation comprises an index keyword, an index category, and recommendation content based at least in part on the reference data, and

wherein the index keyword comprises a keyword of the reference data, wherein the index category composes a search category of the reference data, and wherein the recommendation content comprises a category, an attribute, or a combination of the category and the attribute corresponding to the clicking data having a greatest value in the reference data.

13. The method as recited in claim 2, wherein a user behavior log is generated based at least in part on the user behavior information, wherein the user behavior log comprises a search log, a product clicking log, a purchase log, and a navigation area clicking log, wherein the search log comprises times of searches, a first set of user-entered keywords, and search categories, wherein further the product clicking log comprises times of clicks, a second set of user-entered keywords, and selected products, wherein the purchase log comprises times of purchases and a third set of user-entered keywords, and wherein the navigation area clicking log comprises times of clicks in the navigation area, a fourth set of user-entered keywords, and selected categories.

14. A system comprising:

a memory that stores machine instructions;

a display device; and

a processor that executes the machine instructions to;

send a user inquiry to a server; and

receive a recommendation result responsive to the user inquiry, wherein the recommendation result corresponds to the user inquiry and comprises types of content, wherein said types of content of the recommendation result are obtained based at least in part on one or more types of content included in the user inquiry, wherein further a navigation dictionary is compiled based upon user behavior information associated with a user of the system, and the recommendation result is sent to the system from the server responsive to the user inquiry being located in the navigation dictionary.

15. The system as recited in claim 14, wherein the navigation dictionary is compiled by:

generating reference data based at least in part on statistics obtained from the user behavior information;

compiling the reference data to obtain an editor recommendation corresponding to the user behavior information; and

compiling the editor recommendation into a navigation dictionary.

16. The system as recited in claim 15, wherein the user inquiry comprises a search keyword, and wherein the editor recommendation comprises an index keyword and recommendation content.

17. The system as recited in claim 16, wherein the editor recommendation is searched for in the navigation dictionary based at least in part, on the search keyword, and the recommendation content is used as the recommendation result.

18. The system as recited in claim 15, wherein the user inquiry comprises a search keyword, and wherein the editor recommendation comprises an index keyword, a recommendation type, and recommendation content, and wherein the machine instructions cause the processor to:

display the recommendation content on an on-screen user interlace of the display device based at least in part on a format according to the recommendation type.

19. The system as recited in claim 15, wherein the machine instructions cause the processor to:

send user feedback information corresponding to the editor recommendation to the server; and

receive an indication that the editor recommendation is valid based at least in part on the user feedback information.

20. The system as recited in claim 15, wherein the machine instruction cause the processor to:

send user feedback information corresponding to the editor recommendation to the server; and

receive a modified editor recommendation responsive to a determination that the editor recommendation is invalid.