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Using negative voting to diversify answers in non-factoid question answering
Conference proceeding

Using negative voting to diversify answers in non-factoid question answering

Palakorn Achananuparp, Christopher Yang, Xin Chen and Xiaoli Chen
Proceedings of the 18th ACM conference on information and knowledge management, pp 1681-1684
02 Nov 2009
DOI: https://doi.org/10.1145/1645953.1646203

Abstract

answer ranking negative voting non-factoid question answering
We propose a ranking model to diversify answers of non-factoid questions based on an inverse notion of graph connectivity. By representing a collection of candidate answers as a graph, we posit that novelty, a measure of diversity, is inversely proportional to answer vertices' connectivity. Hence, unlike the typical graph ranking models, which score vertices based on the degree of connectedness, our method assigns a penalty score for a candidate answer if it is strongly connected to other answers. That is, any redundant answers, indicated by a higher inter-sentence similarity, will be ranked lower than those with lower inter-sentence similarity. At the end of the ranking iterations, many redundant answers will be moved toward the bottom on the ranked list. The experimental results show that our method helps diversify answer coverage of non-factoid questions according to F-scores from nugget pyramid evaluation.

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7 citations in Scopus

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