INFERENCE OF QUERY RELATIONSHIPS

• US 20090070323A1
• Filed: 08/29/2008
• Published: 03/12/2009
• Est. Priority Date: 09/12/2007
• Status: Active Grant

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Sundaresan, Neelakantan, Parikh, Nishith
• Granted Patent: US 8,086,620 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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.

Claims

1. 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;

relating the first query to the second query based on the identifying of the at least one common term;

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.

2. The method of claim 1, wherein the identifying of the at least one common term is based on a textual similarity match.

3. The method of claim 1, wherein the first query and the second query are submitted to locate an item for purchase.

4. The method of claim 1, further comprising identifying a number of the at least one dissimilar term, wherein the weight is based on the number of the at least one dissimilar term.

5. The method of claim 1, further comprising:

identifying a first number of the at least one dissimilar term that is included in the first query;

identifying a second number of the at least one dissimilar term that is included in the second query,

wherein the weight is based on a difference between the first number and the second number.

6. The method of claim 5, wherein the difference is based on a direction traversed between the first query and the second query.

7. The method of claim 1, further comprising building an inverted index from the first query and the second query.

8. The method of claim 7, wherein the at least one common term and the at least one dissimilar term are identified from the inverted index.

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

comparing a plurality of first terms included in a first query with a plurality of second terms included in a second query;

identifying at least one common term between the first query and the second query based on the operation of comparing the plurality of first terms with the plurality of second terms;

relating the first query to the second query based on the identifying of the at least one common term;

identifying at least one dissimilar term between the first query and the second query based on the operation of comparing the plurality of first terms with the plurality of second terms; and

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

10. The machine-readable medium of claim 9, wherein the operation of identifying the at least one common term is based on a textual similarity match.

11. The machine-readable medium of claim 9, wherein the instructions, when performed by the machine, cause the machine to perform operations comprising:

identifying a first number of the at least one dissimilar term that is included in the first query;

identifying a second number of the at least one dissimilar term that is included in the second query; and

subtracting the first number from the second number to define a difference, the weight being based on the difference.

12. The machine-readable medium of claim 9, wherein the instructions, when performed by the machine, cause the machine to perform operations comprising building an inverted index from the first query and the second query.

13. The machine-readable medium of claim 12, wherein the at least one common term and the at least one dissimilar term are identified from the inverted index.

14. 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;

identifying at least one common term between a plurality of first terms included in a first query and a plurality of second terms included in a second query;

relating the first query to the second query based on the operation of identifying the at least one common term;

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

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

15. The processing system of claim 14, wherein the operation of identifying the at least one common term is based on a textual similarity match.

16. The processing system of claim 14, wherein the instructions, that when executed by the at least one processor, cause further operations to be performed, comprising identifying a number of the at least one dissimilar term, wherein the weight is based on the number of the at least one dissimilar term.

17. The processing system of claim 14, wherein the instructions, that when executed by the at least one processor, cause further operations to be performed, comprising:

identifying a first number of the at least one dissimilar term that is included in the first query;

identifying a second number of the at least one dissimilar term that is included in the second query,

wherein the weight is based on a difference between the first number and the second number.

18. The processing system of claim 17, wherein the instructions, that when executed by the at least one processor, cause further operations to be performed, comprising subtracting the first number from the second number to define the difference, the subtracting being based on a direction traversed from the first query to the second query.

19. The processing system of claim 17, wherein the instructions, that when executed by the at least one processor, cause further operations to be performed, comprising subtracting the second number from the first number to define the difference, the subtracting being based on a direction traversed from the second query to the first query.

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

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

relating the first query to the second query based on the identifying that the first query and the second query are associated with the single search session;

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.

21. The method of claim 20, wherein the single search session is defined by a series of queries inputted within a predefined time period.

22. The method of claim 20, wherein the first query and the second query are related based on a purchase of an item within the single search session.

23. The method of claim 20, wherein the first query and the second query are inputted consecutively.

24. The method of claim 20, further comprising storing the first query and the second query in a data structure comprised of other plurality of queries provided by other users, wherein the number of the plurality of other search sessions that include the first query and the second query is identified from the data structure.

25. The method of claim 20, wherein the first query and the second query are related based on the first query and the second query being included in at least three of the plurality of other search sessions.

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

identifying that a first query and a second query are inputted consecutively within a first single search session by a first user;

relating the first query to the second query based on the identifying that the first query and the second query are inputted within the first single search session;

accessing a third query and a fourth query that are inputted consecutively within a second single search session by a second user, the third query being related to the fourth query;

identifying a match between the second query and the third query; and

relating the first query to the fourth query based on the identifying of the match between the second query and the third query.

27. The machine-readable medium of claim 26, wherein the instructions, when performed by the machine, cause the machine to perform operations comprising:

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

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

28. The machine-readable medium of claim 27, wherein the instructions, when performed by the machine, cause the machine to perform operations comprising storing the first query and the second query in a data structure comprised of other plurality of queries provided by other users, wherein the number of the plurality of other search sessions that include the first query and the second query is identified from the data structure.

29. The machine-readable medium of claim 26, wherein the identifying of the match is based on a textual similarity match of the second query with the third query.

30. The machine-readable medium of claim 26, wherein the first single search session is defined by a series of queries inputted within a predefined time period.

31. The machine-readable medium of claim 26, wherein the first query and the second query are related based on a purchase of an item within the first single search session.

32. The machine-readable medium of claim 26, wherein the first query and the second query are related based on the first query and the second query being included in at least one of the plurality of other search sessions.

33. 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;

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

relating the first query to the second query based on the identifying that the first query and the second query are associated with the single search session;

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

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

34. The processing system of claim 33, wherein the single search session is defined by a series of queries inputted within a predefined time period.

35. The processing system of claim 33, wherein the first query and the second query are related based on a purchase of an item within the single search session.

36. The processing system of claim 33, wherein the first query and the second query are inputted consecutively.

37. The processing system of claim 33, wherein the instructions, that when executed by the at least one processor, cause further operations to be performed, comprising storing the first query and the second query in a data structure comprised of other plurality of queries associated with the plurality of other search sessions provided by other users, wherein the number of the plurality of other search sessions that include the first query and the second query is identified from the data structure.

38. The processing system of claim 33, wherein the first query and the second query are related based on the first query and the second query being included in at least three of the plurality of other search sessions.