Vertical Search-Based Query Method, System and Apparatus

• US 20140122468A1
• Filed: 01/06/2014
• Published: 05/01/2014
• Est. Priority Date: 04/30/2010
• Status: Abandoned Application

• Current Assignee: Alibaba Group Holding Ltd.
• Original Assignee: Alibaba Group Holding Ltd.
• Inventors: Mo, Yi, Fu, Qile, Xiao, He, Nie, Xuping, Ning, Wei
• Application Number:
  US14/148,440
• Publication Number:
  US 20140122468A1
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Various embodiments of a method, system, and apparatus related to query based on vertical search are disclosed. In one aspect, a method of query based on vertical search receives a user query. The method obtains a first category model from a category model warehouse based on the user query to generate a first query result. The first category model includes one or more commodity categories that correspond to one or more keywords in the user query. The method also obtains one or more commodity categories corresponding to the user query from a commodity warehouse to generate a second query result. The method further generates a final query result by combining the first query result and the second query result.

Claims

1. A method comprising:

obtaining a first category model from a category model warehouse for a query to generate a first query result, the first category model including one or more commodity categories that correspond to one or more keywords in the query;

obtaining one or more commodity categories corresponding to the query from a commodity warehouse to generate a second query result; and

generating a final query result by combining the first query result and the second query result.

2. A method as recited in claim 1, further comprising:

receiving the query from a user;

transmitting the final query result to the user;

generating a log based on the query and the user'"'"'s clicking operations in response to the final query result;

generating a second category model from statistical analysis of data in the log; and

updating the category model warehouse with the second category model.

3. A method as recited in claim 1, wherein the first category model comprises one or more attribute categories corresponding to the one or more commodity categories, and wherein generating the second query result comprises obtaining one or more commodity categories and associated attribute categories that match the query.

4. A method as recited in claim 1, wherein, when the query comprises one or more keywords inputted by a user, obtaining the first category model comprises:

determining whether a keyword corresponding to the first category model matches at least one of the one or more keywords in the query;

in an event that the keyword corresponding to the first category model matches at least one of the one or more keywords in the query;

obtaining a second category model that matches the at least one keyword of the one or more keywords in the query;

in an event that no keyword corresponding to the first category model matches any of the one or more keywords in the query;

revising the one or more keywords in the query and repeating the determining until a third category model that matches at least one of the revised one or more keywords in the query is obtained; and

generating the first query result using the second category model or the third category model.

5. A method as recited in claim 1, wherein, when the query comprises one or more keywords inputted by a user and one or more commodity categories selected by the user, obtaining the first category model comprises:

determining whether a keyword corresponding to the first category model matches at least one of the one or more keywords in the query;

in an event that the keyword corresponding to the first category model matches at least one of the one or more keywords in the query;

obtaining a second category model that matches the at least one keyword of the one or more keywords in the query;

in an event that the keyword corresponding to the first category model does not match any of the one or more keywords in the user query;

revising the one or more keywords in the user query and repeating the determining until a third category model that matches at least one of the revised one or more keywords in the user query is obtained; and

obtaining a fourth category model that matches the one or more commodity categories selected by the user from the second category model or the third category model; and

generating the first query result using commodity categories in the fourth category model.

6. A method as recited in claim 1, wherein generating the final query result comprises:

obtaining a first combined result comprising a plurality of commodity categories that are included in both the first query result and the second query result, the first combined result further comprising weights corresponding to the plurality of commodity categories in the first combined result and being a combination of respective weights from the first query result and from the second query result;

obtaining a second combined result comprising commodity categories and weights in the second query result;

increasing the weights in the first combined result to render the weights corresponding to the plurality of commodity categories in the first combined result to be respectively higher than the weights corresponding to the commodity categories in the second combined result; and

arranging the plurality of commodity categories in the first combined result according to the weights in the first combined result.

7. A method as recited in claim 1, wherein generating the final query result comprises:

obtaining a first combined result comprising a plurality of commodity categories and associated attribute categories that are in both the first query result and the second query result, the first combined result further comprising weights corresponding to the plurality of commodity categories and the associated attribute categories in the first combined result and being a combination of respective weights from the first query result and the second query result;

obtaining a second combined result comprising commodity categories and associated attribute categories in the second query result, the second combined result further comprising weights corresponding to the commodity categories and the associated attribute categories in the second query result;

increasing the weights in the first combined result to render the weights corresponding to the plurality of commodity categories and the associated attribute categories in the first combined result to be respectively higher than the weights corresponding to the commodity categories and the associated attribute categories in the second combined result; and

arranging the plurality of commodity categories and the associated attribute categories in the first combined result according to the weights in the first combined result.

8. A method as recited in claim 2, wherein generating the log comprises:

obtaining data on the user'"'"'s clicking operations with respect to at least one of the one or more commodity categories, attribute categories corresponding to the at least one of the one or more commodity categories, and commodities in response to the final query result;

generating the log based on the data on the user'"'"'s clicking operations, the log comprising the query and clicking information, the clicking information comprising one or more of;

a commodity category and an attribute category of a commodity selected by the user; and

storing the generated log.

9. A method as recited in claim 2, wherein generating the second category model comprises:

obtaining a statistical analysis result based on statistical analysis of the query and clicking information in the log, the statistical analysis result comprising a plurality of commodity categories, associated attribute categories, and weights corresponding to the plurality of commodity categories and the associated attribute categories that correspond to the query, the weights being related to number of clicks on the plurality of commodity categories and the associated attribute categories, clicking probability related to the plurality of commodity categories and the associated attribute categories, or a combination thereof; and

arranging the statistical analysis result as a category tree to generate the second category model.

10. A method as recited in claim 9, wherein arranging the statistical analysis result comprises:

determining whether the weights reach one or more weight thresholds; and

in an event that the weights reach the one or more weight thresholds, generating the second category model based on the plurality of commodity categories, the associated attribute categories, and the weights.

11. A query system based on a vertical search, comprising:

a query server that;

obtains a first category model from a category model warehouse for a query to generate a first query result, the first category model including one or more first commodity categories that correspond to one or more keywords in the query;

obtains one or more second commodity categories corresponding to the query from a commodity warehouse to generate a second query result; and

generates a final query result by combining the first query result and the second query result;

a log server that generates a log based on the query and user'"'"'s clicking operations in response to the final query result; and

a modeling server that generates a second category model from statistical analysis of data in the log.

12. A query system as recited in claim 11, wherein the modeling server transmits the second category model to the query server, wherein the query server provides the final query result to a user, and updates the category model warehouse with the second category model.

13. A query system as recited in claim 11, wherein the first category model comprises one or more attribute categories corresponding to the one or more first commodity categories, and wherein the query server obtains a commodity category and an attribute category corresponding to the query from the commodity warehouse.

14. A query system as recited in claim 11, wherein:

the query server obtains data of the user'"'"'s clicking operations with respect to a commodity, category and an attribute category corresponding to a commodity in response to the final query result,

the log server generates the log based on the data of the user'"'"'s clicking operations, the log comprising the query and clicking information, the clicking information comprising the commodity category and the attribute category corresponding to the commodity, and wherein the log server further stores the generated log.

15. A query system as recited in claim 11, wherein the modeling server further:

obtains a statistical analysis result based on statistical analysis of the query and clicking information in the log, the statistical analysis result comprising a plurality of commodity categories, associated attribute categories, and weights corresponding to the plurality of commodity categories and the associated attribute categories that correspond to the query, the weights being related to one or more of;

number of clicks on the plurality of commodity categories and the associated attribute categories, and clicking probability related to the plurality of commodity categories and the associated attribute categories; and

arranges the statistical analysis result as a category tree to generate the second category model.

16. A query system as recited in claim 15, wherein the modeling server further:

determines whether the weights reach one or more weight thresholds; and

in an event that the weights reach the one or more weight thresholds, generates the second category model based on the plurality of commodity categories, the associated attribute categories, and the weights.

17. A query server, comprising:

an acquisition module that obtains a user query;

a query module that, based on the user query, retrieves a category model matching the user query from a category model warehouse, generates a first query result based on the category model, and searches for commodity categories that match the user query in a commodity warehouse to generate a second search result, the category model comprising one or more commodity categories corresponding to one or more keywords in the user query; and

a combination module that combines the first query result and the second query result to generate a final query result.

18. A query server as recited in claim 17, further comprising a transmission module that:

transmits the final query result to a user;

generates a log based on the user query and the user'"'"'s clicking operations in response to the final query result;

generates a second category model from statistical analysis of data in the log; and

updates the category model warehouse with the second category model.

19. A server as recited in claim 17, wherein the first category model further comprises one or more attribute categories corresponding to the one or more commodity categories, and wherein the query module obtains a commodity category and an associated attribute category that match the user query.