Inference of query relationships based on retrieved attributes

• US 8,655,868 B2
• Filed: 08/29/2008
• Issued: 02/18/2014
• Est. Priority Date: 09/12/2007
• Status: Active Grant

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Parikh, Nishith, Sundaresan, Neelakantan
• Primary Examiner(s): Cao, Phuong Thao
• Application Number:
  US12/202,185
• Publication Number:
  US 20090070299A1
• Time in Patent Office: 1,999 Days
• Field of Search: 707/721, 707/722, 707/5, 707/999.005
• US Class Current: 707/721
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/3349 Reuse of stored results of previous queries
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]

Abstract

Various example embodiments are provided for inferring relationships between queries. In an example, queries are related based on the identification of common terms between the queries. Another example is to relate queries based on the identification that the queries are associated with a single search session. Yet another example is to infer relationships based on the identification of relationships between item attributes retrieved from the submission of the queries.

Claims

1. A method of inferring a relationship between a first query and a second query, the method comprising:

accessing a first attribute of a first item retrieved from the first query, the first attribute being a property belonging to the first item that is extracted based on buying behavior of at least one user as a result of a submission of the first query;

accessing a second attribute of a second item retrieved from the second query, the second attribute being a property belonging to the second item that is extracted based on buying behavior of at least one user as a result of a submission of the second query;

identifying, using at least one processor, a further relationship between the first attribute and the second attribute that are extracted based on the buying behaviors;

relating the first query to the second query based on the identifying of the further relationship between the first attribute and the second attribute; and

assigning a weight to the relationship between the first query and the second query that is derived from a weight assigned to the first attribute and a weight assigned to the second attribute.

2. The method of claim 1, wherein the weight assigned to the first attribute is incremented each time the first item is purchased as a result of a submission of the first query and the weight assigned to the second attribute is incremented each time the second item is purchased as a result of a submission of the second query.

3. The method of claim 1, wherein the weight assigned to the relationship is based on a dot product between the first attribute and the second attribute.

4. The method of claim 1, wherein the identifying of the further relationship is based on a textual similarity match of the first attribute with the second attribute.

5. The method of claim 1, wherein the identifying of the further relationship is based on an identification of the first attribute being semantically related to the second attribute.

6. The method of claim 1, wherein the first attribute is defined in a title associated with the first item.

7. The method of claim 1, wherein the first attribute is a category associated with the first item.

8. The method of claim 1, wherein the first attribute is a brand associated with the first item.

9. The method of claim 1, wherein the first item is a purchase resulting from a search based on the first query.

10. A non-transitory machine-readable medium that stores instructions which, when performed by a machine, cause the machine to perform operations comprising:

accessing a plurality of first attributes of a first item retrieved from a search based on the first query, each of the plurality of first attributes being a property belonging to the first item that is extracted based on buying behavior of at least one user as a result of a submission of the first query;

accessing a plurality of second attributes of a second item retrieved from a search based on the second query, each of the plurality of second attributes being a property belonging to the second item that is extracted based on buying behavior of at least one user as a result of a submission of the second query;

identifying at least one semantically related attribute between the plurality of first attributes and the plurality of second attributes that are extracted based on the buying behaviors;

relating the first query to the second query based on the identifying of the at least one semantically related attribute; and

assigning a weight to a relationship between the first query and the second query that is derived from a weight assigned to the plurality of first attributes and a weight assigned to the plurality of second attributes.

11. The non-transitory machine-readable medium of claim 10, wherein a plurality of first terms included in the first query is dissimilar to a plurality of second terms included in the second query.

12. The non-transitory machine-readable medium of claim 10, wherein less than twenty six of the plurality of first attributes are accessed and less than twenty six of the plurality of second attributes are accessed.

13. The non-transitory machine-readable medium of claim 10, wherein the weight assigned to the relationship is based on a dot product between the plurality of first attributes and the plurality of second attributes.

14. The non-transitory machine-readable medium of claim 10, wherein the first query is inputted by a user and the second query is inputted by a different user.

15. A processing system comprising:

at least one processor; and

a memory in communication with the at least one processor, the memory being configured to store a relationship identification module that is executable by the at least one processor, the relationship identification module having instructions that, when executed by the at least one processor, cause operations to be performed, comprising;

accessing a first attribute of a first item retrieved from a first query, the first attribute being a property belonging to the first item that is extracted based on buying behavior of at least one user as a result of a submission of the first query;

accessing a second attribute of a second item retrieved from a second query, the second attribute being a property belonging to the second item that is extracted based on buying behavior of at least one user as a result of a submission of the second query;

identifying a relationship between the first attribute and the second attribute that are extracted based on the buying behaviors;

relating the first query to the second query based on the identifying of the relationship between the first attribute and the second attribute; and

assigning a weight to a further relationship between the first query and the second query that is derived from a weight assigned to the first attribute and a weight assigned to the second attribute.

16. The processing system of claim 15, wherein the weight assigned to the first attribute is incremented each time the first item is purchased as a result of a submission of the first query and the weight assigned to the second attribute is incremented each time the second item is purchased as a result of a submission of the second query.

17. The processing system of claim 15, wherein the weight assigned to the further relationship is based on a dot product between the first attribute and the second attribute.

18. The processing system of claim 15, wherein the operation of identifying the relationship is based on a textual similarity match of the first attribute with the second attribute.

19. The processing system of claim 15, wherein the operation of identifying the relationship is based on an identification of the first attribute being semantically related to the second attribute.

20. A method of inferring a relationship between a first query comprising a plurality of first terms and a second query comprising a plurality of second terms, the method comprising:

identifying at least one common term between the plurality of first terms and the plurality of second terms;

identifying that the first query and the second query are associated with a single search session;

accessing a first attribute of a first item retrieved from the first query, the first attribute being a property belonging to the first item that is extracted based on buying behavior of at least one user as a result of a submission of the first query;

accessing a second attribute of a second item retrieved from the second query, the second attribute being a property belonging to the second item that is extracted based on buying behavior of at least one user as a result of a submission of the second query;

identifying, using at least one processor, a further relationship between the first attribute and the second attribute that are extracted based on the buying behaviors;

relating the first query to the second query based on at least one of the identifying of at least one common term, the identifying that the first query and the second query are associated with a single search session or the identifying of the further relationship between the first attribute and the second attribute; and

in response to the relating the first query to the second query being based on the identifying of the further relationship between the first attribute and the second attribute, assigning a weight to the relationship between the first query and the second query that is derived from a weight assigned to the first attribute and a weight assigned to the second attribute.

21. The method of claim 20, further comprising:

identifying at least one dissimilar term between the plurality of first terms and the plurality of second terms; and

assigning a weight to the relationship between the first query and the second query based on the identifying of the at least one dissimilar term.

22. The method of claim 20, further comprising:

identifying a number of a plurality of other search sessions that include the first query and the second query; and

assigning a weight to the relationship between the first query and the second query based on the number of the plurality of other search sessions.

23. The method of claim 20, further comprising assigning a weight to the relationship between the first query and the second query based on a dot product between the first attribute and the second attribute.