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Title:
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A Relevance-based Theoretical Foundation for Question Answering
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Author:
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Marco De Boni
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Email:
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click here to access email
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Degree Awarded:
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University of York
, Department of Computer Science
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Degree Date:
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2004
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Linguistic Subfield(s):
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Applied Linguistics
Computational Linguistics
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Director(s):
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Suresh Manandhar
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Abstract:
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While there is a very large amount of written information available in electronic format, there is no easy way to automatically find a reliable answer to simple questions such as 'Who is the president of the US?'. Research in Question Answering (QA) systems address these issues by trying to find a method for answering a question by searching for a precise response in a collection of documents. Current systems are no more than prototypes, and, while there is agreement amongst researchers on the generic aim of QA systems, little work has been done on clarifying the problem beyond the establishment of a standard evaluation framework. There is consequently a significant lack of theoretical understanding of QA systems and a considerable amount of confusion about their aims and evaluation.
This thesis addresses the need for a theoretical investigation into QA systems by employing the notion of relevance to clarify their purpose and elucidate their constituent structure, showing how the theory developed can be applied in practice.
Initially we examine the concept of answerhood as applicable open domain QA systems and we argue that there are limits as to what can be considered an answer to a question. In order to understand the nature of these limits we examine the concept of relevance, showing that to talk about an answer is really to speak about the relevance of that answer in relation to a question; we maintain that it is misleading to talk about absolutely correct or incorrect answers: we should instead be referring to answers which are more or less relevant to a question. We then examine the concept of relevance, illustrating how it is composed of semantic relevance, dealing with the relationship in meaning between question and answer; goal-directed relevance, dealing with questioner and answerer goals; logical relevance, dealing with the more formal relationship which considers whether an answer provides the information which the question sought; and morphic relevance, dealing with the form an answer takes in relation to a question.
From the notion of relevance we built a model of QA systems which illustrates the constraints under which they operate: we show how an answer is constrained by the questioner and the answerer’s prior knowledge, goals, rules of inference, answer form preferences, as well as the questioner and the answerer’s approach to giving relevance judgements from the point of view of semantic, goal-directed, logical, morphic and overall relevance.
We then illustrate how the framework can be used to improve current TREC-style QA systems by considering each component of relevance individually and implementing that component starting from a 'standard' TREC-style QA system, YorkQA
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