项目名称: 基于协同计算的社区问答意见型问题分析与答案生成研究
项目编号: No.61303180
项目类型: 青年科学基金项目
立项/批准年度: 2014
项目学科: 自动化技术、计算机技术
项目作者: 周光有
作者单位: 华中师范大学
项目金额: 28万元
中文摘要: 社区问答是Web 2.0背景下产生的一种新的以"提问-回答"为主的信息共享和交流方式。不同于传统的自动问答,社区问答以"用户"为中心,具有明显的协同性,用户与文本内容(问答对)之间存在着复杂的信息关联,文本内容与用户标签协同以及用户交互反过来赋予文本内容更丰富的语义。社区问答中意见型问题占有很大比重,严重制约了社区问答分析的智能化水平。但是目前已有的研究工作主要集中在事实型问题的分析、答案检索以及用户行为建模等方面,对意见型问题分析和答案生成的研究工作相对较少,特别是缺乏系统性的研究。本申请课题以社区问答中意见型问题分析与答案生成为研究对象,以协同计算为研究方法,研究内容包括:(1)融合社会关联和协同计算的用户问题情感极性分析;(2)基于稀疏表达和分布式计算的相似问题协同检索;(3)基于局部关联和协同分析的答案自动生成。本申请课题的研究成果将为问答系统以及意见型问题的分析提供参考。
中文关键词: 自然语言处理;问答系统;信息抽取;社区问答;观点分析
英文摘要: Community question answering is a new information sharing and interactive way based on "asking-answering" in Web 2.0. Different from traditional automatic question answering, community question answering is based on "users", users and text contents have complex informative relationships, text contents and user labels collaborate with each other, and user interactivity makes the text contents more meaningful. Opinion questions have a large proportion in community question answering, which greatly hinders the intelligent level of community question answering analysis. However, the current research mainly focues on the analysis of factoid questions,answer retrieval and user behaviors, the research work on opinion question analysis and answer generation is relative small, especially for lack of systematic research. This project aims to study the opinion question analysis and answer generation using the collaborative computing method, the research tasks include: (1) users' questions polarity analysis based on social relationships and collaborative computing; (2)similar question collaborative retrieval based on sparse representation and distributional computing; (3) answer automatic generation based on local relationship and collaborative analysis. The achievements of this project will provide valuable suggestion for
英文关键词: Natural Language Processing;Question Answering;Information Extraction;Community Question Answering;Opinion Mining