QUESTION-ANSWERING SYSTEM AND METHOD BASED ON SEMANTIC LABELING OF TEXT DOCUMENTS AND USER QUESTIONS
First Claim
1. A method for question-answering based on automatic semantic labeling of text documents and user questions, the method comprising:
- providing at least one computer processor coupled to at least one non-transitory storage medium, the at least one computer processor performing the method, including;
electronically receiving natural language text documents;
electronically receiving a user question formulated in a natural language;
performing a basic linguistic analysis of the text documents and the user question;
performing semantic labeling of the text documents through semantic analysis, and storing the semantically labeled text documents in a labeled text documents database;
performing semantic labeling of the user question through semantic analysis;
searching the labeled text documents database for text fragments relevant to the semantically labeled user question, wherein relevance is based on a ranking of the text fragments relative to the semantically labeled user question; and
synthesizing answers to the user question from the relevant text fragments, and electronically presenting the synthesized answer to the user.
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Abstract
A question-answering system for searching exact answers in text documents provided in the electronic or digital form to questions formulated by user in the natural language is based on automatic semantic labeling of text documents and user questions. The system performs semantic labeling with the help of markers in terms of basic knowledge types, their components and attributes, in terms of question types from the predefined classifier for target words, and in terms of components of possible answers. A matching procedure makes use of mentioned types of semantic labels to determine exact answers to questions and present them to the user in the form of fragments of sentences or a newly synthesized phrase in the natural language. Users can independently add new types of questions to the system classifier and develop required linguistic patterns for the system linguistic knowledge base.
155 Citations
28 Claims
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1. A method for question-answering based on automatic semantic labeling of text documents and user questions, the method comprising:
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providing at least one computer processor coupled to at least one non-transitory storage medium, the at least one computer processor performing the method, including; electronically receiving natural language text documents; electronically receiving a user question formulated in a natural language; performing a basic linguistic analysis of the text documents and the user question; performing semantic labeling of the text documents through semantic analysis, and storing the semantically labeled text documents in a labeled text documents database; performing semantic labeling of the user question through semantic analysis; searching the labeled text documents database for text fragments relevant to the semantically labeled user question, wherein relevance is based on a ranking of the text fragments relative to the semantically labeled user question; and synthesizing answers to the user question from the relevant text fragments, and electronically presenting the synthesized answer to the user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A computer program product comprising a computer-readable medium having stored therein computer-executable instructions for performing a method for question-answering based on automatic semantic labeling of text documents and user questions, the method comprising:
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electronically receiving natural language text documents; electronically receiving a user question formulated in a natural language; performing a basic linguistic analysis of the text documents and the user question; performing semantic labeling of the text documents through semantic analysis, and storing the semantically labeled text documents in a labeled text documents database; performing semantic labeling of the user question through semantic analysis; searching the labeled text documents database for text fragments relevant to the semantically labeled user question, wherein relevance is based on a ranking of the text fragments relative to the semantically labeled user question; and synthesizing answers to the user question from the relevant text fragments. - View Dependent Claims (16)
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17. A question-answering system that uses automatic semantic labeling of text documents and a user question in electronic or digital form formulated in natural language, the system comprising:
a linguistic knowledge base and a linguistic analyzer that produce linguistically analyzed text documents and user question, the linguistic analyzer comprising a semantic analyzer comprising; an expanded Subject-Action-Object (eSAO) recognizer and a Cause-Effect recognizer that produce semantically analyzed text documents and user question, including recognizing one or more facts in the form of one or more eSAO sets based on the text documents and user question, wherein eSAO and Cause-Effect recognition is based on patterns stored in the linguistic knowledge base. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
Specification