Cognitive Search Operation

Patent metadata

Field	Value
Publication number	US-2018307992-A1
Application number	US-201715714328-A
Country	US
Kind code	A1
Filing date	Sep 25, 2017
Priority date	Apr 20, 2017
Publication date	Oct 25, 2018
Grant date	—

Abstract

A method, system and computer readable medium for performing a cognitive search operation comprising: receiving training data, the training data comprising information based upon user interaction with cognitive attributes; performing a machine learning operation on the training data; generating a cognitive profile based upon the information generated by performing the machine learning operation; and, performing a cognitive search operation on a corpus of content based upon the cognitive profile, the cognitive search operation returning cognitive results specific to the cognitive profile of the user.

First claim

What is claimed is:

1 . A computer-implementable method for performing a cognitive search operation comprising:
receiving training data, the training data comprising information based upon user interaction with cognitive attributes; performing a machine learning operation on the training data; generating a cognitive profile based upon the information generated by performing the machine learning operation; and, performing a cognitive search operation on a corpus of content based upon the cognitive profile, the cognitive search operation returning cognitive results specific to the cognitive profile of the user.

2 . The method of claim 1 , wherein:
the results specific to the user are further refined based upon terms used when performing the cognitive search operation.

3 . The method of claim 2 , wherein:
a second user having a second cognitive profile and performing a search using the terms used when performing the cognitive search operation would return cognitive results specific to the second cognitive profile.

4 . The method of claim 1 , wherein:
the machine learning operation comprises a ranked insight model operation, the ranked insight operation comprising a factor-needs operation.

5 . The method of claim 1 , wherein:
the machine learning operation comprises a hierarchical topic model operation, the hierarchical topic model operation comprises a domain topic abstraction operation and a hierarchical topic operation.

6 . The method of claim 1 , wherein:
the cognitive profile is continuously updated based upon at least one of a plurality of feedback information sources, the feedback information sources comprising information based upon feedback from interactions between the user and the cognitive insight and learning system, information from a query submitted by the user to the cognitive insight and learning system, information from external input data, information from a user navigating a hierarchical topic model and information received from a training system.

7 . A system comprising:
a processor; a data bus coupled to the processor; and a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for:
receiving training data, the training data comprising information based upon user interaction with cognitive attributes;
performing a machine learning operation on the training data;
generating a cognitive profile based upon the information generated by performing the machine learning operation; and,
performing a cognitive search operation on a corpus of content based upon the cognitive profile, the cognitive search operation returning cognitive results specific to the cognitive profile of the user.

8 . The system of claim 7 , wherein:
the results specific to the user are further refined based upon terms used when performing the cognitive search operation.

9 . The system of claim 8 , wherein:
a second user having a second cognitive profile and performing a search using the terms used when performing the cognitive search operation would return cognitive results specific to the second cognitive profile.

10 . The system of claim 7 , wherein:
the plurality of machine learning operation comprise a ranked insight model operation, the ranked insight operation comprising a factor-needs operation.

11 . The system of claim 7 , wherein:
the machine learning operation comprises a hierarchical topic model operation, the hierarchical topic model operation comprises a domain topic abstraction operation and a hierarchical topic operation.

12 . The system of claim 7 , wherein:
the cognitive profile is continuously updated based upon at least one of a plurality of feedback information sources, the feedback information sources comprising information based upon feedback from interactions between the user and the cognitive insight and learning system, information from a query submitted by the user to the cognitive insight and learning system, information from external input data, information from a user navigating a hierarchical topic model and information received from a training system.

13 . A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:
receiving training data, the training data comprising information based upon user interaction with cognitive attributes; performing a machine learning operation on the training data; generating a cognitive profile based upon the information generated by performing the machine learning operation; and, performing a cognitive search operation on a corpus of content based upon the cognitive profile, the cognitive search operation returning cognitive results specific to the cognitive profile of the user.

14 . The non-transitory, computer-readable storage medium of claim 13 , wherein:
the results specific to the user are further refined based upon terms used when performing the cognitive search operation.

15 . The non-transitory, computer-readable storage medium of claim 14 , wherein:
a second user having a second cognitive profile and performing a search using the terms used when performing the cognitive search operation would return cognitive results specific to the second cognitive profile.

16 . The non-transitory, computer-readable storage medium of claim 13 , wherein:
the plurality of machine learning operation comprise a ranked insight model operation, the ranked insight operation comprising a factor-needs operation.

17 . The non-transitory, computer-readable storage medium of claim 13 , wherein:
the machine learning operation comprises a hierarchical topic model operation, the hierarchical topic model operation comprises a domain topic abstraction operation and a hierarchical topic operation.

18 . The non-transitory, computer-readable storage medium of claim 13 , wherein:
the cognitive profile is continuously updated based upon at least one of a plurality of feedback information sources, the feedback information sources comprising information based upon feedback from interactions between the user and the cognitive insight and learning system, information from a query submitted by the user to the cognitive insight and learning system, information from external input data, information from a user navigating a hierarchical topic model and information received from a training system.

19 . The non-transitory, computer-readable storage medium of claim 13 , wherein the computer executable instructions are deployable to a client system from a server system at a remote location.

20 . The non-transitory, computer-readable storage medium of claim 13 , wherein the computer executable instructions are provided by a service provider to a user on an on-demand basis.

Assignees

• Chawla Neeraj
• Sanchez Matthew
• Ricaurte Andrea M
• Ranatunga Dilum
• Acharya Ayan
• Lindsley Hannah R
• Cognitive Scale Inc

Inventors

• Chawla Neeraj
• Sanchez Matthew
• Ricaurte Andrea M
• Ranatunga Dilum
• Acharya Ayan
• Lindsley Hannah R

Classifications

• G06N20/00 Primary

  Machine learning · CPC title

• G06N5/04

  Inference or reasoning models · CPC title

• G06F16/5854

  using shape and object relationship · CPC title

• G06N5/022

  Knowledge engineering; Knowledge acquisition · CPC title

• G06F16/243

  Natural language query formulation · CPC title