TRANSLATING NATURAL LANGUAGE QUERIES

• US 20130080472A1
• Filed: 09/28/2011
• Published: 03/28/2013
• Est. Priority Date: 09/28/2011
• Status: Abandoned Application

• Current Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Original Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Inventors: Cohen, Ira, Mordechai, Eli, Assulin, Ohad, Dakar, Refael
• Application Number:
  US13/247,266
• Publication Number:
  US 20130080472A1
• Time in Patent Office: Days
• US Class Current: 707/794
• CPC Class Codes: G06F 16/243 Natural language query formulation

Abstract

A system and related method to process natural queries is provided. In one aspect, it is determined whether any portion of the natural language query matches one of a plurality of semantic keywords. In another aspect, the natural language query is translated into at least one database query. In a further aspect, the database query may be executed in a database arranged in accordance with the database model.

Claims

1. A system comprising:

at least one processor to;

receive a natural language query;

determine whether any portion of the natural language query matches one of a plurality of semantic keywords, each semantic keyword representing at least one attribute of a database model, the plurality of semantic keywords comprising synonymous semantic keywords, the synonymous semantic keywords representing at least one identical attribute of the database model to disambiguate ambiguous words in the natural language query;

translate the natural language query into at least one database query, the at least one database query using a unique combination of attributes of the database model, each attribute in the unique combination being represented by a semantic keyword that matches any portion of the natural language query;

to rank the at least one database query based on a relevancy of each database query such that the relevancy is further based on a number of one to one associations between the unique combination of attributes and the semantic keywords that match portions of the natural language query; and

execute the at least one database query in a database arranged in accordance with the database model.

3. The system of claim 1, wherein the unique combination of attributes included in a highest ranked database query causes the at least one processor to generate a result that is most relevant to the natural language query when the highest ranked database query is executed therein.

5. The system of claim 1, wherein the at least one processor is a processor to:

apply a hash function to each semantic keyword so as to associate each semantic keyword with a hash code; and

associate each hash code with the at least one attribute of the database model.

7. The system of claim 1, wherein the at least one attribute is a database table, a database column, or a database value.

2. (canceled)

4. (canceled)

6. (canceled)

8. A method comprising:

receiving, using at least one processor, a natural language query;

determining, using the at least one processor, whether any portion of the natural language query matches one of a plurality of semantic keywords, each semantic keyword representing at least one attribute of a database model, the plurality of semantic keywords comprising synonymous semantic keywords, the synonymous semantic keywords representing at least one identical attribute of the database model to disambiguate ambiguous words in the natural language query;

translating, using the at least one processor, the natural language query into at least one database query, the at least one database query using a unique combination of attributes of the database model, each attribute in the unique combination being represented by a semantic keyword that matches any portion of the natural language query;

ranking, using the at least one processor, the at least one database query based on a relevancy of each database query such that the relevancy is further based on a number of one to one associations between the unique combination of attributes and the semantic keywords that match portions of the natural language query; and

executing, using the at least one processor, the at least one database query in a database arranged in accordance with the database model.

10. The method of claim 8, wherein the unique combination of attributes included in a highest ranked database query causes the at least one processor to generate a result that is most relevant to the natural language query when the highest ranked database query is executed therein.

12. The method of claim 8, further comprising

applying, using the at least one processor, a hash function to each semantic keyword so as to associate each semantic keyword with a hash code;

and

associating, using the at least one processor, each hash code with the at least one attribute of the database model.

14. The method of claim 8, wherein the at least one attribute is a database table, a database column, or a database value.

9. (canceled)

11. (canceled)

13. (canceled)

15. A non-transitory computer readable medium having instructions stored therein, which if executed, cause at least one processor to:

receive a natural language query;

determine whether any portion of the natural language query matches one of a plurality of semantic keywords, each semantic keyword representing at least one attribute of a database model, the plurality of semantic keywords comprising synonymous semantic keywords, the synonymous semantic keywords representing at least one identical attribute of the database model to disambiguate ambiguous words in the natural language query;

translate the natural language query into a at least one database query, the at least one database query using a unique combination of attributes of the database model, each attribute in the unique combination being represented by a semantic keyword that matches any portion of the natural language query;

rank the at least one database query based on a relevancy of each database query such that the relevancy is further based on a number of one to one associations between the unique combination of attributes and the semantic keywords that match portions of the natural language query; and

execute the at least one database query in a database arranged in accordance with the database model.

17. The non-transitory computer readable medium of claim 15, wherein the unique combination of attributes included in a highest ranked database query causes the at least one processor to generate a result that is most relevant to the natural language query when the highest ranked database query is executed therein.

19. The non-transitory computer readable medium of claim 15, wherein the instructions if executed further cause the at least one processor to:

apply a hash function to each semantic keyword so as to associate each semantic keyword with a hash code; and

associate each hash code with the at least one attribute of the database model.

16. (canceled)

18. (canceled)

20. (canceled)