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Predictive Query Index For Natural Language Query Interfaces

Abstract: System and method for creating a predictive query index for natural language query interfaces are disclosed. In an example, at least one activity is dynamically identified. The activity includes adding of a new entity instance, adding of a new query pattern or adding of a new entity type. Further, at least one predictive query associated with the at least one activity is created when the at least one activity is dynamically identified. Furthermore, the at least one predictive query is validated based on pre-defined ontological constraints associated with the at least one activity. Moreover, the predictive query index for the natural language query interfaces is created with the at least one predictive query based on the validation.

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Notices, Deadlines & Correspondence

Patent Information

Application #
Filing Date
10 February 2016
Publication Number
43/2017
Publication Type
INA
Invention Field
COMPUTER SCIENCE
Status
Email
iprdel@lakshmisri.com
Parent Application
Patent Number
Legal Status
Grant Date
2024-03-12
Renewal Date

Applicants

TATA CONSULTANCY SERVICES LIMITED
Nirmal Building, 9th Floor, Nariman Point, Mumbai-400021, Maharashtra, India

Inventors

1. MULLAKKARA AZHUVATH, Rajeev
Tata Consultancy Services, TCS Center Infopark, Kochi 682030, Kerala, India
2. MADHAVAN, Manoj
Tata Consultancy Services, TCS Center Infopark, Kochi 682030, Kerala, India

Specification

Claims:1. A computer implemented method comprising:
dynamically identifying at least one activity, wherein the activity comprises adding of a new entity instance, adding of a new query pattern or adding of a new entity type;
creating at least one predictive query associated with the at least one activity when the at least one activity is dynamically identified;
validating the at least one predictive query based on pre-defined ontological constraints associated with the at least one activity; and
creating a predictive query index for natural language query interfaces with the at least one predictive query based on the validation.

2. The method as claimed in claim 1, wherein creating the at least one predictive query associated with the activity of adding of the new entity instance is dynamically identified, comprises:
identifying query patterns related to the new entity instance; and
creating the at least one predictive query associated with the new entity instance based on the identified query patterns.

3. The method as claimed in claim 2, wherein identifying the query patterns related to the new entity instance, comprises:
searching a pattern index comprising query patterns related to multiple entity instances to identify the query patterns related to the new entity instance.

4. The method as claimed in claim 1, wherein creating the at least one predictive query associated with the activity of adding of the new entity type is dynamically identified, comprises:
identifying query patterns related to the new entity type; and
creating the at least one predictive query associated with the new entity type based on the identified query patterns.

5. The method as claimed in claim 4, wherein identifying the query patterns related to the new entity type, comprises:
searching a pattern index comprising query patterns related to multiple entity types to identify the query patterns related to the new entity type.

6. The method as claimed in claim 1, wherein creating the at least one predictive query associated with the activity of adding of the new query pattern is dynamically identified, comprises:
identifying an entity instance and an entity type satisfying the new query pattern; and
creating the at least one predictive query associated with the entity instance and the entity type based on the new query pattern.

7. The method as claimed in claim 1, wherein the pre-defined ontological constraints comprise constraints based on at least one of entity type relationships and entity instances relationships.

8. A system comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor, wherein the memory includes a predictive query index creation module to:
dynamically identify at least one activity, wherein the activity comprises adding of a new entity instance, adding of a new query pattern or adding of a new entity type;
create at least one predictive query associated with the at least one activity when the at least one activity is dynamically identified;
validate the at least one predictive query based on pre-defined ontological constraints associated with the at least one activity; and
create a predictive query index for natural language query interfaces with the at least one predictive query based on the validation.

9. The system as claimed in claim 8, wherein the predictive query index creation module is configured to:
identify query patterns related to the new entity instance; and
create the at least one predictive query associated with the new entity instance based on the identified query patterns.

10. The system as claimed in claim 9, wherein the predictive query index creation module is configured to:
search a pattern index comprising query patterns related to multiple entity instances to identify the query patterns related to the new entity instance.

11. The system as claimed in claim 8, wherein the predictive query index creation module is configured to:
identify query patterns related to the new entity type; and
create the at least one predictive query associated with the new entity type based on the identified query patterns.

12. The system as claimed in claim 11, wherein the predictive query index creation module is configured to:
search a pattern index comprising query patterns related to multiple entity types to identify the query patterns related to the new entity type.

13. The system as claimed in claim 8, wherein the predictive query index creation module is configured to:
identify an entity instance and an entity type satisfying the new query pattern; and
create the at least one predictive query associated with the entity instance and the entity type based on the new query pattern.

14. The system as claimed in claim 8, wherein the pre-defined ontological constraints comprise constraints based on at least one of entity type relationships and entity instances relationships.
, Description:N/A

Documents

Application Documents

# Name Date
1 Form 5 [10-02-2016(online)].pdf 2016-02-10
2 Form 3 [10-02-2016(online)].pdf 2016-02-10
3 Form 18 [10-02-2016(online)].pdf 2016-02-10
4 Drawing [10-02-2016(online)].pdf 2016-02-10
5 Description(Complete) [10-02-2016(online)].pdf 2016-02-10
6 201621004795-FORM 26-12-04-2016.pdf 2016-04-12
7 201621004795-COREESPONDENCE-12-04-2016.pdf 2016-04-12
8 ABSTRACT1.jpg 2018-08-11
9 201621004795-Form 1-250216.pdf 2018-08-11
10 201621004795-Correspondence-250216.pdf 2018-08-11
11 201621004795-FER.pdf 2020-02-19
12 201621004795-FORM-26 [27-07-2020(online)].pdf 2020-07-27
13 201621004795-OTHERS [19-08-2020(online)].pdf 2020-08-19
14 201621004795-FER_SER_REPLY [19-08-2020(online)].pdf 2020-08-19
15 201621004795-COMPLETE SPECIFICATION [19-08-2020(online)].pdf 2020-08-19
16 201621004795-CLAIMS [19-08-2020(online)].pdf 2020-08-19
17 201621004795-ABSTRACT [19-08-2020(online)].pdf 2020-08-19
18 201621004795-US(14)-HearingNotice-(HearingDate-08-01-2024).pdf 2023-12-15
19 201621004795-Correspondence to notify the Controller [19-12-2023(online)].pdf 2023-12-19
20 201621004795-Correspondence to notify the Controller [04-01-2024(online)].pdf 2024-01-04
21 201621004795-FORM-26 [05-01-2024(online)].pdf 2024-01-05
22 201621004795-Written submissions and relevant documents [23-01-2024(online)].pdf 2024-01-23
23 201621004795-PatentCertificate12-03-2024.pdf 2024-03-12
24 201621004795-IntimationOfGrant12-03-2024.pdf 2024-03-12

Search Strategy

1 search004795_10-02-2020.pdf
2 amdsearch004795AE_06-04-2021.pdf

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