Method And System For Maintaining Knowledge Required In A Decision-Making Process Framework

• US 20180113903A1
• Filed: 10/19/2017
• Published: 04/26/2018
• Est. Priority Date: 10/20/2016
• Status: Active Grant

• Current Assignee: DIWO LLC
• Original Assignee: Loven Systems, LLC
• Inventors: RANA, Satyendra Pal, KEERTHY, Chandra Puttanna, KALLAKURI, Krishna Prakash
• Granted Patent: US 10,621,169 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/14 Details of searching files based on file metadata
• CPC Class Codes: G06F 16/24535 of sub-queries or views
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

Disclosed is a knowledge system for retrieving a knowledge object, pertaining to a query, in a cognitive decision-making process. The knowledge system comprises a knowledge access module and a knowledge processing module. The knowledge access module may receive a knowledge request requesting a knowledge object. In one aspect, the knowledge request may be associated to at least one domain. The knowledge access further generates a structured query based on the knowledge request. The knowledge access module further splits the structured query into one or more sub queries. In one aspect, the structured query may be split based on the at least one domain and metadata associated to the at least one domain. The knowledge access module further fetches one or more knowledge objects for each sub query upon executing the one or more sub queries on a system database storing a plurality of knowledge objects. In one aspect, the one or more knowledge objects may be fetched upon referring to one or more ontologies stored in the system database. The knowledge processing module creates and thereby stores an integrated knowledge object for the knowledge request upon integrating the one or more knowledge objects fetched by the one or more sub queries.

Claims

1. A method for retrieving a knowledge object, pertaining to a query, in a cognitive decision-making process, the method comprising:

receiving, by a processor, a knowledge request requesting a knowledge object, wherein the knowledge request is associated to at least one domain, and wherein the knowledge request is received from a user;

generating, by the processor, a structured query based on the knowledge request;

splitting, by the processor, the structured query into one or more sub queries, wherein the structured query is split based on the at least one domain and metadata associated to the at least one domain;

fetching, by the processor, one or more knowledge objects for each sub query upon executing the one or more sub queries on a system database storing a plurality of knowledge objects, wherein the one or more knowledge objects are fetched upon referring to one or more ontologies stored in the system database;

creating, by the processor, an integrated knowledge object for the knowledge request upon integrating the one or more knowledge objects fetched by the one or more sub queries; and

storing, the processor, the integrated knowledge object, along with the one or more ontologies, in a temporary memory for the user'"'"'s reference thereby retrieving the knowledge object pertaining to the query.

2. The method of claim 1, wherein the structured query is generated by using machine learning methods comprising a deep learning pre-trained network for the knowledge request and a structured query language.

3. The method of claim 1, wherein the structured query is generated as one of a Structured Query Language (SQL) and SPARQL.

4. The method of claim 1, wherein the metadata indicates one or more sub sections associated to the at least one domain.

5. The method of claim 1, wherein the one or more ontologies comprises a set of predefined rules facilitating fetching of a knowledge object relevant for a sub query, and wherein the set of predefined rules comprises relationship among domains and a set of scenarios indicating a change in the relationship among the domains over a period of time.

6. The method of claim 1, wherein each sub query is assigned with an actor responsible for fetching at least one knowledge object, from the system database, relevant for a sub query and thereby storing the at least one knowledge object in the temporary memory, and wherein the actor indicates a mathematical model for performing computations.

7. A knowledge system for retrieving a knowledge object, pertaining to a query, in a cognitive decision-making process, the knowledge system comprising:

a processor; and

a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, and wherein the plurality of modules comprising

a knowledge access module for

receiving a knowledge request requesting a knowledge object, wherein the knowledge request is associated to at least one domain, and wherein the knowledge request is received from a user,

generating a structured query based on the knowledge request,

splitting the structured query into one or more sub queries, wherein the structured query is split based on the at least one domain and metadata associated to the at least one domain,

fetching one or more knowledge objects for each sub query upon executing the one or more sub queries on a system database storing a plurality of knowledge objects, wherein the one or more knowledge objects are fetched upon referring to one or more ontologies stored in the system database; and

a knowledge processing module for

creating an integrated knowledge object for the knowledge request upon integrating the one or more knowledge objects fetched by the one or more sub queries, and

storing the integrated knowledge object, along with the one or more ontologies, in a temporary memory for the user'"'"'s reference thereby retrieving the knowledge object pertaining to the query.

8. The knowledge system of claim 7, wherein the structured query is generated by using machine learning methods comprising a deep learning pre-trained network for the knowledge request and a structured query language.

9. The knowledge system of claim 7, wherein the structured query is generated as one of a Structured Query Language (SQL) and SPARQL.

10. The knowledge system of claim 7, wherein the metadata indicates one or more sub sections associated to the at least one domain.

11. The knowledge system of claim 7, wherein the one or more ontologies comprises a set of predefined rules facilitating fetching of a knowledge object relevant for a sub query, and wherein the set of predefined rules comprises relationship among domains and a set of scenarios indicating a change in the relationship among the domains over a period of time.

12. The knowledge system of claim 7, wherein each sub query is assigned with an actor responsible for fetching at least one knowledge object, from the system database, relevant for a sub query and thereby storing the at least one knowledge object in the temporary memory, and wherein the actor indicates a mathematical model for performing computations.

13. A non-transitory computer readable medium embodying a program executable in a computing device for retrieving a knowledge object, pertaining to a query, in a cognitive decision-making process, the program comprising a program code:

a program code for receiving a knowledge request requesting a knowledge object, wherein the knowledge request is associated to at least one domain, and wherein the knowledge request is received from a user;

a program code for generating a structured query based on the knowledge request;

a program code for splitting the structured query into one or more sub queries, wherein the structured query is split based on the at least one domain and metadata associated to the at least one domain;

a program code for fetching one or more knowledge objects for each sub query upon executing the one or more sub queries on a system database storing a plurality of knowledge objects, wherein the one or more knowledge objects are fetched upon referring to one or more ontologies stored in the system database;

a program code for creating an integrated knowledge object for the knowledge request upon integrating the one or more knowledge objects fetched by the one or more sub queries; and

a program code for storing the integrated knowledge object, along with the one or more ontologies, in a temporary memory for the user'"'"'s reference thereby retrieving the knowledge object pertaining to the query.