问题焦点提取和答案段落检索

Amine Bayoudhi, Lamia Hadrich Belguith, Hatem Ghorbel
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引用次数: 2

摘要

问题分析是问答系统(QAS)中的一项重要工作。它一般包括识别问题的语义类型和提取问题的主要焦点。目标是通过问题更好地指定所需的信息。在这种背景下,作为旨在为政治辩论实施阿拉伯意见问答的框架的一部分,本文解决了定义意见问题焦点的问题,并特别提出了一种提取态度问题焦点的方法。该方法基于半自动构造的词典句法模式。此外,本文提出了一种基于向量空间模型(VSM)的自适应方法,从电视政治节目中检索候选人的回答段落。实验结果表明,焦点提取方法的持有者和目标提取F1得分均达到了72%以上,基线通道检索任务提高了25%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Question focus extraction and answer passage retrieval
Question Analysis is an important task in Question Answering Systems (QAS). It consists generally in identifying the semantic type of the question and extracting the main focus of the question. The goal is to better specify the required information by the question. In this context and as part of a framework aiming to implement an Arabic opinion QAS for political debates, this paper addresses the problem of defining the focus of opinion questions and proposes particularly an approach for extracting the focus of attitude questions. The proposed approach is based on semi-automatically constructed lexico-syntactic patterns. Furthermore, the paper presents an adapted Vector Space Model (VSM) based method to retrieve candidate answer passages from a transcribed TV political show. Several experiments were carried out and showed that the focus extraction approach has achieved over 72% as F1 score for holder and target extraction, and has improved the baseline passage retrieval task by over than 25%.
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