关键词: 问答社区, 碎片化回复文本, 自动抽取, 聚类, 相异度

Abstract:  In response to the problem of effectively extracting the required text information from fragmented reply texts in Q&A communities， this paper proposes a clustering method for fragmented reply texts based on dissimilarity matrix. Firstly， the clustering center is designed based on dissimilarity between texts and the fragmented reply texts in the community are classified by the clustering way. Then， the text features of user questions are extracted based on RNN+CNN. Finally， the automatic extraction of fragmented response text is achieved based on TF-IDF algorithm using the extracted question text features. The experimental results show that the proposed method can automatically extract the required text information with high accuracy and stability， and can be applied to the extraction of fragmented reply texts in question answering communities.

Key words: question-answer community, fragmented reply text, automatic extraction, clustering, dissimilarity