SYSTEM AND METHOD FOR DETERMINING QUERY INTENT

• US 20140309993A1
• Filed: 04/10/2013
• Published: 10/16/2014
• Est. Priority Date: 04/10/2013
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Inventors: Goussard, Jacques-Olivier
• Granted Patent: US 9,373,322 B2
• Time in Patent Office: Days
• US Class Current: 704/231
• CPC Class Codes: G06F 16/33 Querying
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 40/20 Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G10L 15/063 Training

Abstract

A method for training a system is provided. The method may include storing one or more backend communication logs, each of the one or more backend communication logs including a user query and a corresponding backend query. The method may further include parsing the one or more backend communication logs to extract statistical information and generating a mapping between each user query and a corresponding set of language tags. The method may also include sorting the one or more backend communication logs based upon, at least in part, the extracted statistical information.

Claims

1. A computer-implemented method for training a system comprising:

storing, using one or more computing devices, one or more backend communication logs, each of the one or more backend communication logs including a user query and a corresponding backend query;

parsing, using the one or more computing devices, the one or more backend communication logs to extract statistical information;

generating, using the one or more computing devices, a mapping between each user query and a corresponding set of language tags; and

sorting, using the one or more computing devices, the one or more backend communication logs based upon, at least in part, the extracted statistical information.

2. The method of claim 1, further comprising:

receiving, using the one or more computing devices, a current user query and the corresponding backend query.

3. The method of claim 1, wherein the extracted statistical information includes at least one of high runner queries and data priors.

4. The method of claim 1 further comprising:

translating the extracted information into a natural language tag.

5. The method of claim 1 wherein the extracted statistical information includes at least one of mandatory fields, optional fields, and disambiguation templates.

6. The method of claim 5 wherein the extracted statistical information includes a disambiguation template configured to group one or more user queries and their corresponding backend queries belonging to the same task context.

7. The method of claim 6 further comprising:

extracting interaction templates from the groups of one or more user queries and their corresponding backend queries.

8. The method of claim 1 wherein parsing the one or more backend communication logs includes parsing an SQL communication log.

9. The method of claim 1, wherein parsing the one or more backend communication logs includes parsing a REST communication log.

10. A non-transitory computer readable storage medium having stored thereon instructions that when executed by a processor perform one or more operations, the operations comprising:

storing, using one or more computing devices, one or more backend communication logs, each of the one or more backend communication logs including a user query and a corresponding backend query;

parsing, using the one or more computing devices, the one or more backend communication logs to extract statistical information;

generating, using the one or more computing devices, a mapping between each user query and a corresponding set of language tags; and

sorting, using the one or more computing devices, the one or more backend communication logs based upon, at least in part, the extracted statistical information.

11. The non-transitory computer readable storage medium of claim 10, wherein operations further comprise:

receiving, using the one or more computing devices, a current user query and the corresponding backend query.

12. The non-transitory computer readable storage medium of claim 10, wherein the extracted statistical information includes at least one of high runner queries and data priors.

13. The non-transitory computer readable storage medium of claim 10 wherein operations further comprise:

translating the extracted information into a natural language tag.

14. The non-transitory computer readable storage medium of claim 10 wherein the extracted statistical information includes at least one of mandatory fields, optional fields, and disambiguation templates.

15. The non-transitory computer readable storage medium of claim 14 wherein the extracted statistical information includes a disambiguation template configured to group one or more user queries and their corresponding backend queries belonging to the same task context.

16. The non-transitory computer readable storage medium of claim 15 wherein operations further comprise:

extracting interaction templates from the groups of one or more user queries and their corresponding backend queries.

17. The non-transitory computer readable storage medium of claim 10 wherein parsing the one or more backend communication logs includes parsing an SQL communication log.

18. The non-transitory computer readable storage medium of claim 10, wherein parsing the one or more backend communication logs includes parsing a REST communication log.

19. A system comprising:

one or more processors configured to execute one or more operations, the operations including;

storing, using one or more computing devices, one or more backend communication logs, each of the one or more backend communication logs including a user query and a corresponding backend query;

parsing, using the one or more computing devices, the one or more backend communication logs to extract statistical information;

generating, using the one or more computing devices, a mapping between each user query and a corresponding set of language tags; and

sorting, using the one or more computing devices, the one or more backend communication logs based upon, at least in part, the extracted statistical information.

20. The system of claim 19 wherein the one or more processors are further configured to translate the extracted information into a natural language tag.