Generating answer variants based on tables of a corpus
First Claim
1. A method, in a data processing system comprising a processor and a memory, the method comprising:
- configuring the processor, based on instructions loaded into the memory and executed by the processor, to implement a candidate answer variant engine, that operates in conjunction with a Question Answering (QA) cognitive computing system to generate an answer output in response to the QA cognitive computing system receiving an input question from a client computing device, wherein configuring the processor further comprises configuring the processor to implement an element grouping engine and an element grouping similarity analysis engine of the candidate answer variant engine;
receiving, by the candidate answer variant engine, from a QA processing pipeline of the QA cognitive computing system based on computerized natural language processing of the input question, an indication of a structured portion of content in a corpus of electronic content processed by the QA cognitive computing system to answer input questions;
generating, by the element grouping engine of the candidate answer variant engine, a plurality of groupings of elements of the structured portion of content;
generating, by the element grouping engine of the candidate answer variant engine, for each grouping of elements in the plurality of groupings of elements, and for each element in the grouping of elements, a corresponding grouping vector representation, corresponding to the element;
for each grouping vector representation of each grouping of elements in the plurality of groupings of elements;
performing, by the element grouping similarity analysis engine of the candidate answer variant engine, a similarity measure calculation between the grouping vector representation and a vector representation of the input question; and
selecting, by the element grouping similarity analysis engine of the candidate answer variant engine, an element corresponding to the grouping vector representation for inclusion as a candidate answer variant in a candidate answer variant data structure based on results of the similarity measure calculation;
performing, by the QA cognitive computing system, question answering operations for answering the input question based on a cognitive analysis, by the QA processing pipeline of the QA cognitive computing system, of one or more candidate answer variants in the candidate answer variant data structure; and
outputting, by the QA cognitive computing system, a final answer to the client computing device based on results of performing the question answering operations.
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Accused Products
Abstract
Mechanisms are provided for implementing a candidate answer variant engine. The mechanisms receive an indication of a structured portion of content in a corpus, generate a plurality of groupings of elements of the structured portion of content, and generate, for each grouping of elements in the plurality of groupings of elements, and for each element in the grouping of elements, a corresponding grouping vector representation, corresponding to the element. The mechanisms, for each grouping vector representation of each grouping of elements in the plurality of groupings of elements perform a similarity measure calculation between the grouping vector representation and a vector representation of an input question, and select an element corresponding to the grouping vector representation for inclusion as a candidate answer variant based on results of the similarity measure calculation. The mechanisms perform question answering operations based on an analysis of one or more candidate answer variants.
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Citations
20 Claims
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1. A method, in a data processing system comprising a processor and a memory, the method comprising:
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configuring the processor, based on instructions loaded into the memory and executed by the processor, to implement a candidate answer variant engine, that operates in conjunction with a Question Answering (QA) cognitive computing system to generate an answer output in response to the QA cognitive computing system receiving an input question from a client computing device, wherein configuring the processor further comprises configuring the processor to implement an element grouping engine and an element grouping similarity analysis engine of the candidate answer variant engine; receiving, by the candidate answer variant engine, from a QA processing pipeline of the QA cognitive computing system based on computerized natural language processing of the input question, an indication of a structured portion of content in a corpus of electronic content processed by the QA cognitive computing system to answer input questions; generating, by the element grouping engine of the candidate answer variant engine, a plurality of groupings of elements of the structured portion of content; generating, by the element grouping engine of the candidate answer variant engine, for each grouping of elements in the plurality of groupings of elements, and for each element in the grouping of elements, a corresponding grouping vector representation, corresponding to the element; for each grouping vector representation of each grouping of elements in the plurality of groupings of elements; performing, by the element grouping similarity analysis engine of the candidate answer variant engine, a similarity measure calculation between the grouping vector representation and a vector representation of the input question; and selecting, by the element grouping similarity analysis engine of the candidate answer variant engine, an element corresponding to the grouping vector representation for inclusion as a candidate answer variant in a candidate answer variant data structure based on results of the similarity measure calculation; performing, by the QA cognitive computing system, question answering operations for answering the input question based on a cognitive analysis, by the QA processing pipeline of the QA cognitive computing system, of one or more candidate answer variants in the candidate answer variant data structure; and outputting, by the QA cognitive computing system, a final answer to the client computing device based on results of performing the question answering operations. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:
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configure the computing device, based on instructions loaded into a memory and executed by a processor of the computing device, to implement a candidate answer variant engine, that operates in conjunction with a Question Answering (QA) cognitive computing system to generate an answer output in response to the QA cognitive computing system receiving an input question from a client computing device, wherein configuring the computing device further comprises configuring the computing device to implement an element growing engine and an element grouping similarity analysis engine of the candidate answer variant engine; receive, by the candidate answer variant engine, from a QA processing pipeline of the QA cognitive computing system based on computerized natural language processing of the input question, an indication of a structured portion of content in a corpus of electronic content processed by the QA cognitive computing system to answer input questions an indication of a structured portion of content in a corpus; generate, by the element grouping engine of the candidate answer variant engine, a plurality of groupings of elements of the structured portion of content; generate, by the element grouping engine of the candidate answer variant engine, for each grouping of elements in the plurality of groupings of elements, and for each element in the grouping of elements, a corresponding grouping vector representation, corresponding to the element, of each of the other elements in the grouping of elements; for each grouping vector representation of each grouping of elements in the plurality of groupings of elements; perform, by the element grouping similarity analysis engine of the candidate answer variant engine, a similarity measure calculation between the grouping vector representation and a vector representation of the input question; and select, by the element grouping similarity analysis engine of the candidate answer variant engine, an element corresponding to the grouping vector representation for inclusion as a candidate answer variant in a candidate answer variant data structure based on results of the similarity measure calculation; perform, by the QA cognitive computing system, question answering operations for answering the input question based on a cognitive analysis, by the QA processing pipeline of the QA cognitive computing system, of one or more candidate answer variants in the candidate answer variant data structure; and output, by the QA cognitive computing system a final answer to the client computing device based on results of performing the question answering operations. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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20. An apparatus comprising:
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a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to; configure the processor to implement a candidate answer variant engine, that operates in conjunction with a Question Answering (QA) cognitive computing system to generate an answer output in response to the QA cognitive computing system receiving an input question from a client computing device, wherein configuring the processor further comprises configuring the processor to implement an element grouping engine and an element grouping similarity analysis engine of the candidate answer variant engine; receive, by the candidate answer variant engine, from a QA processing pipeline of the QA cognitive computing system based on computerized natural language processing of the input question, an indication of a structured portion of content in a corpus of electronic content processed by the QA cognitive computing system to answer input questions an indication of a structured portion of content in a corpus; generate, by the element grouping engine of the candidate answer variant engine, a plurality of groupings of elements of the structured portion of content; generate, by the element grouping engine of the candidate answer variant engine, for each grouping of elements in the plurality of groupings of elements, and for each element in the grouping of elements, a corresponding grouping vector representation, corresponding to the element, of each of the other elements in the grouping of elements; for each grouping vector representation of each grouping of elements in the plurality of groupings of elements; perform, by the element grouping similarity analysis engine of the candidate answer variant engine, a similarity measure calculation between the grouping vector representation and a vector representation of the input question; and select, by the element grouping similarity analysis engine of the candidate answer variant engine, an element corresponding to the grouping vector representation for inclusion as a candidate answer variant in a candidate answer variant data structure based on results of the similarity measure calculation; perform, by the QA cognitive computing system, question answering operations for answering the input question based on a cognitive analysis, by the QA processing pipeline of the QA cognitive computing system, of one or more candidate answer variants in the candidate answer variant data structure; and output, by the QA cognitive computing system, a final answer to the client computing device based on results of performing the question answering operations.
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Specification