System and method for learning answers to frequently asked questions from a semi-structured data source
First Claim
1. A method comprising:
- retrieving, from a memory, a global structure and a plurality of candidate answers therein;
computing a first probability of a candidate answer based on a local structure of the candidate answer within the global structure;
computing a second probability of the candidate answer based on content of the candidate answer given content of a query;
computing a third probability of the candidate answer based on context of the candidate answer given the content of the query; and
providing a combined probability of the candidate answer as a function of the first probability, second probability, and third probability.
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Abstract
A frequently-asked-question (FAQ)-based system receives question(s) from a user and generates answer(s) based on data about the question(s). In one embodiment, a method includes retrieving, from a memory, a global structure and candidate answers therein. The method can include computing a first, second, and third probability of a candidate answer based on a local structure of the candidate answer within the global structure, content of the candidate answer given content of a query and context of the candidate answer given the content of the query, respectively. The method can include providing a combined probability of the candidate answer based on the first probability, second probability, and third probability. The method can improve efficiency of a FAQ-based system by automating organization of semi-structured data in a database. Therefore, a human user does not need to manually generate the database when it is already generated in semi-structured form, a semi-structured HTML document.
33 Citations
20 Claims
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1. A method comprising:
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retrieving, from a memory, a global structure and a plurality of candidate answers therein; computing a first probability of a candidate answer based on a local structure of the candidate answer within the global structure; computing a second probability of the candidate answer based on content of the candidate answer given content of a query; computing a third probability of the candidate answer based on context of the candidate answer given the content of the query; and providing a combined probability of the candidate answer as a function of the first probability, second probability, and third probability. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system comprising:
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a processor; and a non-transitory computer-readable medium having encoded thereon a sequence of instructions which, when loaded and executed by the processor, causes the processor to implement; a structure generation module configured to retrieve, from a memory, a global structure and a plurality of candidate answers therein; a computation module including;
(i) a first computation unit configured to compute a first probability of a candidate answer based on a local structure of the candidate answer within the global structure;
(ii) a second computation unit configured to compute a second probability of the candidate answer based on content of the candidate answer given content of a query; and
(iii) a third computation unit configured to compute a third probability of the candidate answer based on context of the candidate answer given the content of the query; anda combination module configured to provide a combined probability for the candidate answer as a function of the first probability, second probability, and third probability. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification