Ranking of Parse Options Using Machine Learning

• US 20170330106A1
• Filed: 10/11/2016
• Published: 11/16/2017
• Est. Priority Date: 05/13/2016
• Status: Abandoned Application

• Current Assignee: Tecnotree Technologies Incorporated
• Original Assignee: Cognitive Scale Inc (Tecnotree Oyj)
• Inventors: Lindsley, Hannah R.
• Application Number:
  US15/290,447
• Publication Number:
  US 20170330106A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06F 16/84 Mapping; Conversion
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/043 Distributed expert systems; Blackboards
• CPC Class Codes: G06N 5/048 Fuzzy inferencing

Abstract

A computer-implementable method for managing a cognitive graph comprising: receiving data from a data source; processing the data, the processing comprising performing a parsing operation on the data, the processing the data identifying a plurality of knowledge elements based upon the parsing operation, the parsing operation comprising ranking of parse options; and, storing the knowledge elements within the cognitive graph as a collection of knowledge elements, the storing universally representing knowledge obtained from the data.

Claims

1. A computer-implementable method for managing a cognitive graph comprising:

receiving data from a data source;

processing the data, the processing comprising performing a parsing operation on the data, the processing the data identifying a plurality of knowledge elements based upon the parsing operation, the parsing operation comprising ranking of parse options; and

,

storing the knowledge elements within the cognitive graph as a collection of knowledge elements, the storing universally representing knowledge obtained from the data.

2. The method of claim 1, further comprising:

providing a parse ranking rule set; and

ranking the parse options using the parse ranking set, the ranking providing a determination of highly ranked parse options.

3. The method of claim 1, further comprising:

providing a parse rule set; and

wherein

using the parse rules set when performing the parsing operation.

4. The method of claim 3, further comprising:

generating a set of parse options by performing the parsing operation using the parse rule set, the parse options representing respective parse trees within a parse forest.

5. The method of claim 4, further comprising:

performing conceptualization processes on the highly ranked parse options to provide a set of conceptualization ambiguity options.

6. The method of claim 5, wherein:

applying a conceptualization rule set to the set of conceptualization ambiguity options; and

,

ranking the set of conceptualization ambiguity options to provide highly ranked conceptualization options.