Question-answering method and question-answering apparatus
First Claim
1. A method implemented by a program being executable by a processor for a question-answering apparatus having communication equipment, a storage for storing a plurality of reply examples and a CPU for performing a reply composition process of replying to the question document by using a reply example selected from the plurality of reply examples, the method comprising the steps of:
- receiving an input of a question document into said communication equipment;
storing in said storage important part keyword frequency information of a keyword of a reply example having an important part, and unimportant part keyword frequency information of a keyword of a reply example having an unimportant part;
dividing said input question document into a plurality of areas;
extracting a plurality of areas from said input question document;
obtaining a likelihood value of a question content corresponding to each of said plurality of stored reply examples for each of said plurality of areas, by using said reply example keyword frequency information;
combining said plurality of areas to provide one or a plurality of important parts in accordance with said likelihood value of said plurality of reply examples obtained for each of said plurality of areas;
calculating an importance degree of each of said plurality of areas by using said important part keyword frequency information;
extracting as an important area an area having said calculated importance degree larger than a predetermined threshold value to obtain a reply example candidate corresponding to said important part by using the plurality of stored reply examples.
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Abstract
A question document is divided into predetermined areas, and it is judged whether each divided area is important, to thereby extract an important area. A reply example candidate likelihood value is calculated for each important area, the likelihood value indicating the degree representative of whether each reply example candidate corresponds to a question content. By using the reply example candidate likelihood value, important areas having similar meanings are combined to extract final important parts. A reply example candidate is selected for each important part from reply example candidates prepared beforehand. A reply example candidate reliability degree representative of certainty of each reply example candidate and a reply composition degree indicating whether it is necessary to compose a new reply are calculated, and by using these values, question documents are distributed to different operator terminals.
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Citations
16 Claims
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1. A method implemented by a program being executable by a processor for a question-answering apparatus having communication equipment, a storage for storing a plurality of reply examples and a CPU for performing a reply composition process of replying to the question document by using a reply example selected from the plurality of reply examples, the method comprising the steps of:
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receiving an input of a question document into said communication equipment; storing in said storage important part keyword frequency information of a keyword of a reply example having an important part, and unimportant part keyword frequency information of a keyword of a reply example having an unimportant part; dividing said input question document into a plurality of areas; extracting a plurality of areas from said input question document; obtaining a likelihood value of a question content corresponding to each of said plurality of stored reply examples for each of said plurality of areas, by using said reply example keyword frequency information; combining said plurality of areas to provide one or a plurality of important parts in accordance with said likelihood value of said plurality of reply examples obtained for each of said plurality of areas; calculating an importance degree of each of said plurality of areas by using said important part keyword frequency information; extracting as an important area an area having said calculated importance degree larger than a predetermined threshold value to obtain a reply example candidate corresponding to said important part by using the plurality of stored reply examples. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A question-answering system having a question-answering apparatus and a reply composition terminal combined via a network to said question-answering apparatus, wherein:
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said question-answering apparatus comprises a communication equipment for receiving an input of a question document, a storage for storing a plurality of reply examples and a processor unit for performing a reply composition process of replying to the question document by using a reply example selected from the plurality of reply examples; said reply composition terminal comprises a communication apparatus for receiving a result of said reply composition process, a display for displaying information contained in said reply composition process result and an input unit for receiving an input for said display information; said storage stores important part keyword frequency information of a keyword of a reply example having an important part, and unimportant part keyword frequency information of a keyword of a reply example having an unimportant part; the processor unit divides said input question document into a plurality of areas; the processor unit of said question-answering apparatus extracts a plurality of areas from said input question document, obtains a likelihood value of a question content corresponding to each of said plurality of stored reply examples for each of said plurality of areas, by using said reply example keyword frequency information, combines said plurality of areas to provide one or a plurality of important parts in accordance with said likelihood value of said plurality of reply examples obtained for each of said plurality of areas, calculates an importance degree of each of said plurality of areas by using said important part keyword frequency information or said unimportant part keyword frequency information, extracts as an important area an area having said calculated importance degree larger than a predetermined threshold value to obtain a reply example candidate corresponding to said important part by using the plurality of stored reply examples to output said reply composition process result. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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Specification