Bag of Grammarとルールベース手法を用いたドメイン依存性の少ないハイブリッド型Whyテキストセグメント判定

摘要

本研究では，Why型質問応答を可能とするための技術の1つである，Why型テキストセグメント判定の精度向上を目的としている．特に，従来手法の1つである，Bag of Grammar手法とルールベース手法を融合することにより，Why型テキストセグメント判定の向上を行うことを目的としている．Bag of Grammar手法では欠落していたWhy型名詞特徴を効果的に取り入れることにより，Why型テキストセグメント判定の向上ができることが分かった．%The main focus of this research is to improve Why Text Segments Classification accuracy for Bag of Grammar method by making use of why-type keywords rules, which extracted manual to construct rule based dictionary, in Rule Based method. The idea behind the usage of Rule Based method is so that it can be supplement the why-type rules that are not covered by Bag of Grammar. We examined two different methods of exploiting Rule Based method to build better Why Text Segments Classification. These methods are differed by the way of combing the Rule Based method into Bag of Grammar method. First model is simply combining features used in Bag of Grammar and Rule Based method to build one feature space to build classifier based on this feature space. Second model explored the schemes of combing different classifiers built by each method to boost the classification accuracy. The experiments showed that some of combing methods provide effective way of constructing more accurate Why Text Segments Classification classifier.