CLASSIFYING E-COMMERCE QUERIES TO GENERATE CATEGORY MAPPINGS FOR DOMINANT PRODUCTS

• US 20140324851A1
• Filed: 04/30/2013
• Published: 10/30/2014
• Est. Priority Date: 04/30/2013
• Status: Abandoned Application

• Current Assignee: Walmart Apollo, LLC (WalMart Inc.)
• Original Assignee: Wal Mart Stores Inc (WalMart Inc.)
• Inventors: Tholiya, Namrata Pramodkumar, Gattani, Abhishek
• Application Number:
  US13/874,023
• Publication Number:
  US 20140324851A1
• Time in Patent Office: Days
• US Class Current: 707/731
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

The present invention extends to methods, systems, and computer program products for classifying e-commerce queries to generate category mappings for dominant products. A query log is mined for any query records with click through information that indicates one or more products were selected from among corresponding query results. For each of one or more categories, a selection rate is calculated for any product selected from among at least one corresponding query result returned in response to a query of the category. A specified top number of products are identified in the category. The specified top number of products has higher selection rates relative to other products in the category. A category score is calculated for the category based on product information associated with the specified top number of products in the category. The one or more categories are ranked based on the calculated category scores.

Claims

1. At a computer system, the computer system including one or more processors and system memory, the computer system communicatively coupled to a query log, the query log including query records for e-commerce queries executed against a product database, each query record containing:

one or more categories that were used as search terms, query results from submitting the one or more category search terms in a query of the product database, and click through information indicating products, if any, that were selected from among the query results, the product database using a plurality of different categories to categorize products, the one or more category search terms selected from among the plurality of categories, a method for classifying e-commerce queries to generate category mappings for dominant products, the method comprising;

mining the query log for any query records with click through information that indicates one or more products were selected from among corresponding query results and that are within a specified date range;

for each of one or more categories selected from among the plurality of categories;

calculating a selection rate for one or more products selected from among at least one corresponding query result returned in response to a query of the category;

identifying a specified top number of products in the category, the specified top number of products having higher selection rates relative to other products in the category;

calculating a category score for the category based on product information associated with the specified top number of products in the category; and

ranking the one or more categories based on the calculated category scores.

2. The method of claim 1, further comprising applying a confidence interval to the identified top number of the products in the category to remove bias from the category score calculations.

3. The method of claim 2, further comprising being able to vary the formula for the confidence interval treatment.

4. The method of claim 1, wherein mining the query log for any query records comprises mining the query log for any query records stored in the query log within the last six months.

5. The method of claim 4, further comprising applying equal weighting to all query records, regardless of date, for the purposes of calculating category scores.

6. The method of claim 1, wherein identifying a specified top number of products in the category comprises identify the top ten products in the category.

7. The method of claim 1, wherein calculating a selection rate comprises calculating a click through rate based on the number of times a product was shown to users and the number of times the product was clicked by users.

8. The method of claim 1, wherein ranking the one or more categories based on the calculated category scores comprises assigning each of the one or more categories to a category type based on the calculated category scores.

9. The method of claim 1, wherein calculating a selection rate for a product comprises calculating a selection rate based on a plurality of categories to which the product is assigned.

10. The method of claim 9, wherein calculating the selection rate comprises considering the product'"'"'s assigned primary category.

11. The method of claim 1, further comprising parsing additional query record details, including, but not limited to, all of the products shown to the user, whether or not the product was added to the cart, whether or not the product was ordered, the order number, the product'"'"'s primary and other category mappings, and the product position in the search results.

12. The method of claim 11, further comprising being able to modify the click through information to consider the additional query record information such as add to cart ratio, order ratio, or product position signals.

13. The method of claim 1, further comprising prior to calculating a selection rate for the one or more products, qualifying the one or more products from among a plurality of products, the plurality of products selected from among at least one corresponding query result returned in response to a query of the category, the one or more products qualified by having one or more of:

a minimum number of clicks and a minimum number of impressions.

14. A computer system for classifying e-commerce queries to generate category mappings for dominant products, the computer system comprising:

one or more processors;

system memory; and

one or more computer storage media having stored thereon computer-executable instructions representing a query classification module, the query classification module configured to;

mine a query log for any query records with click through information that indicates one or more products were selected from among corresponding query results and that are within a specified date range;

for each of one or more categories selected from among the plurality of categories;

calculate a selection rate for any product selected from among at least one corresponding query result returned in response to a query of the category;

identify a specified top number of products in the category, the specified top number of products having higher selection rates relative to other products in the category;

calculate a category score for the category based on product information associated with the specified top number of products in the category; and

rank the one or more categories based on the calculated category scores.

15. The system of claim 14, further comprising the query classification module being configured to apply a confidence interval to remove the bias from the category score calculations.

16. The system of claim 14, wherein the query classification module being configured to mine a query log comprises the query classification module being configured to mine the query log for any query records stored in the query log within the last six months.

17. The system of claim 14, wherein the query classification module being configured to calculate a selection rate comprises the query classification module being configured to calculate a click through rate based on the number of times a product was shown to users and the number of times the product was clicked by users.

18. The system of claim 17, wherein the query classification module being configured to calculate a selection rate comprises the query classification module being configured to calculate a selection rate based on one or more of:

an added to cart ratio, an order ration, and product position signals.

19. A computer program product for use at a computer system, the computer system communicatively coupled to a query log, the query log including query records for e-commerce queries executed against a product database, each query record containing:

one or more categories that were used as search terms, query results from submitting the one or more category search terms in a query of the product database, and click through information indicating products, if any, that were selected from among the query results, the product database using a plurality of different categories to categorize products, the one or more category search terms selected from among the plurality of categories, the computer program product for implementing a method for classifying e-commerce queries to generate category mappings for dominant products, the computer program product comprising one or more computer storage devices having stored thereon computer-executable instructions that when executed at a processor cause the computer system to perform the method including the following;

mine the query log for any query records with click through information that indicates one or more products were selected from among corresponding query results and that are within a specified date range;

for each of one or more categories selected from among the plurality of categories;

calculate a selection rate for any product selected from among at least one corresponding query result returned in response to a query of the category;

identify a specified top number of products in the category, the specified top number of products having higher selection rates relative to other products in the category;

calculate a category score for the category based on product information associated with the specified top number of products in the category; and

rank the one or more categories based on the calculated category scores.

20. The computer program product of claim 19, further comprising computer executable instruction that, when executed, cause the computer system to assign a type to each of the one or more categories.