Method, Apparatus and System of Intelligent Navigation

• US 20130080422A1
• Filed: 01/21/2011
• Published: 03/28/2013
• 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 9,047,341 B2
• Time in Patent Office: Days
• US Class Current: 707/722
• 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 of intelligent navigation, comprising:

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.

2. The method as recited in claim 1, wherein the user inquiry comprises a search keyword, and wherein the editor recommendation comprises an index keyword and recommendation content.

3. The method as recited in claim 2, wherein searching the navigation dictionary based on the user inquiry to obtain the recommended result corresponding to user inquiry comprises:

searching for the editor recommendation in the navigation dictionary based on the search keyword;

obtaining the recommendation content corresponding to the search keyword; and

providing the recommendation content as the recommendation result.

4. The method as recited in claim 1, wherein the user inquiry comprises a search keyword and a search category, and wherein the editor recommendation comprises an index keyword, an index category and recommendation content.

5. The method as recited in claim 4, wherein searching the navigation dictionary based on the user inquiry to obtain the recommended result corresponding to user inquiry comprises:

searching for the editor recommendation in the navigation dictionary based on the search keyword and a the search category;

obtaining the recommendation content corresponding to the search keyword and the search category; and

providing the recommendation content as the recommendation result.

6. The method as recited in claim 1, wherein the user inquiry comprises a search keyword, and wherein the editor recommendation comprises an index keyword, a recommended type, and recommendation content.

7. The method as recited in claim 6, wherein searching the navigation dictionary based on the user inquiry to obtain the recommended result corresponding to user inquiry comprises:

searching for the editor recommendation in the navigation dictionary based on the search keyword;

obtaining the recommendation type and recommendation content corresponding to the search keyword; and

providing the recommendation type and recommendation content as the recommendation result.

8. The method as recited in claim 6, after sending the recommendation result to the client terminal, further comprising:

displaying the recommendation content on a user interface based on a format according to the recommendation type.

9. The method as recited in claim 1, before searching the navigation dictionary based on the user inquiry, further comprising:

obtaining the user behavior information;

providing a user behavior log based on the user behavior information;

generating reference data based on statistics in the user behavior log;

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

compiling the editor recommendation into the navigation dictionary.

10. The method as recited in claim 9, wherein the user behavior log comprises a search log, and wherein the reference data comprises a keyword, a search category, and search data.

11. The method as recited in claim 10, wherein compiling the reference data to obtain the editor recommendation corresponding to the user behavior information comprises:

when the search data of the reference data is greater than a predetermined search threshold, generating the editor recommendation which includes an index keyword, an index category, and recommendation content based on the reference data, wherein the index keyword comprises a keyword of the reference data, the index category comprises a search category of the reference data, and the recommendation content comprises a category, an attribute, or the category and attribute corresponding to the search data having a greatest value in the reference data.

12. The method as recited in claim 9, wherein the user behavior log comprises a clicking log, and wherein the reference data comprises a keyword, a search category, and clicking data.

13. The method as recited in claim 12, wherein compiling the reference data to obtain the editor recommendation corresponding to the user behavior information comprises:

when the clicking data of the reference data is greater than a predetermined clicking threshold, generating the editor recommendation which includes an index keyword, an index category, and recommendation content based on the reference data, wherein the index keyword comprises a keyword of the reference data, the index category comprises a search category of the reference data, and the recommendation content comprises a category, an attribute, or the category and attribute corresponding to the clicking data having a greatest value in the reference data.

14. The method as recited in claim 9, wherein the user behavior log comprises a purchase log, and wherein the reference data comprises a keyword, a search category, and purchase data.

15. The method as recited in claim 14, wherein compiling the reference data to obtain the editor recommendation corresponding to the user behavior information comprises:

when the purchase data of the reference data is greater than a predetermined purchase threshold, generating the editor recommendation which includes an index keyword, an index category, and recommendation content based on the reference data, wherein the index keyword comprises a keyword of the reference data, the index category comprises a search category of the reference data, and the recommendation content comprises a category, an attribute, or the category and attribute corresponding to the purchase data having a greatest value in the reference data.

16. The method as recited in claim 9, after compiling the reference data to obtain the editor recommendation corresponding to the user behavior information, further comprising:

obtaining user feedback information corresponding to the editor recommendation;

determining whether or not the editor recommendation is valid;

keeping the editor recommendation if it is determined to be valid; and

modifying the editor recommendation if it is determined to be invalid.

17. The method as recited in claim 16, wherein the user feedback information comprises a number of clicks corresponding to the editor recommendation and a number of clicks of a given category, and wherein when the number of clicks corresponding to the editor recommendation is smaller than the number of clicks of the given category, the editor recommendation information is determined to be valid.

18. An intelligent navigation server, comprising:

an obtaining module that receives a user inquiry from a client terminal;

an inquiry module that searches 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 which is obtained based on user behavior; and

a transmission module that sends the recommendation result to the client terminal.

19. An intelligent navigation system, comprising:

a navigation dictionary including an editor recommendation based on user behavior information;

a webpage server that receives a user inquiry from a client terminal, sends the user inquiry to an intelligent navigation server, receives a recommendation result from the intelligent navigation server, and sends the recommendation result to the client terminal; and

the intelligent navigation server that receives the user inquiry information from the webpage server, searches the navigation dictionary based on the user inquiry to obtain the recommendation result corresponding to the user inquiry information, and sends the recommendation result to the webpage server.

20. The system as recited in claim 19, further comprising:

a log server that obtains the user behavior information from the webpage server, generates a user behavior log based on the user behavior information, and sends the user behavior log to a storage calculation platform;

the storage calculation platform that stores the user behavior log, generates reference data based on statistics in the user behavior log, calculates an algorithmic recommendation using an intelligent navigation algorithm, provides the reference data and algorithmic recommendation to a back-end database, integrates the editor recommendation and the algorithmic recommendation to provide integrated data, compiles the integrated data into the navigation dictionary, and imports the navigation dictionary into the intelligent navigation server; and

an editing device that edits the reference data, obtains the editor recommendation corresponding to user behavior information, and imports the editor recommendation into the back-end database.