Concept noise reduction in deep question answering systems
First Claim
1. A method, comprising:
- computing a concept score for a first concept in a first case, wherein the concept score is based on whether the first concept is present in at least one of a candidate answer and an item of supporting evidence;
adjusting the concept score based on a coefficient for the first concept in a machine learning concept model for the first concept, wherein the coefficient reflects a relevance of the first concept in generating a correct response to the first case;
excluding the first concept from consideration when analyzing the candidate answer and the item of supporting evidence to generate a response to the first case upon determining at least one of;
(i) that the adjusted concept score does not exceed a predefined minimum weight threshold and (ii) that the coefficient does not exceed a predefined noise threshold; and
considering the first concept when analyzing the candidate answer and the item of supporting evidence to generate the response to the first case upon determining at least one of the concept score and the coefficient exceeds a predefined maximum weight threshold.
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Abstract
Method, computer program product, and system to perform an operation for a deep question answering system. The operation begins by computing a concept score for a first concept in a first case received by the deep question answering system, the concept score being based on a machine learning concept model for the first concept. The operation then excludes the first concept from consideration when analyzing a candidate answer and an item of supporting evidence to generate a response to the first case upon determining that the concept score does not exceed a predefined concept minimum weight threshold. The operation then increases a weight applied to the first concept when analyzing the candidate answer and the item of supporting evidence to generate the response to the first case when the concept score exceeds a predefined maximum weight threshold.
8 Citations
8 Claims
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1. A method, comprising:
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computing a concept score for a first concept in a first case, wherein the concept score is based on whether the first concept is present in at least one of a candidate answer and an item of supporting evidence; adjusting the concept score based on a coefficient for the first concept in a machine learning concept model for the first concept, wherein the coefficient reflects a relevance of the first concept in generating a correct response to the first case; excluding the first concept from consideration when analyzing the candidate answer and the item of supporting evidence to generate a response to the first case upon determining at least one of;
(i) that the adjusted concept score does not exceed a predefined minimum weight threshold and (ii) that the coefficient does not exceed a predefined noise threshold; andconsidering the first concept when analyzing the candidate answer and the item of supporting evidence to generate the response to the first case upon determining at least one of the concept score and the coefficient exceeds a predefined maximum weight threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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Specification