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Received:March 27, 2018 Revised:April 24, 2018
Received:March 27, 2018 Revised:April 24, 2018
中文摘要: 本文以电商平台上的产品评论文本为研究对象，针对产品评论中特征词和观点词的识别问题进行了研究.首先构建特征-观点对二分网络，再给出特征-观点对二分网络中节点重要性排序算法，最后将此算法应用到实际的评论文本数据中以检验算法的有效性.
Abstract:This study takes the product review texts on the e-commerce platform as the mining object, and focuses on the identification of feature words and opinion words in reviews. First, we build bipartite network with feature-opinion words, and give the sorting algorithm of node importance in this network. At last, the algorithm is applied to the actual review text data to verify the effectiveness of the algorithm.
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基金项目:国家自然科学基金（71401107）
引用文本：
刘臣,吉莉,唐莉.基于二分网中心节点识别的产品评论特征-观点词对提取研究.计算机系统应用,2018,27(11):9-16
LIU Chen,JI Li,TANG Li.Research on Product Feature-Opinion Extraction Based on Center Node Recognition in Bipartite Network.COMPUTER SYSTEMS APPLICATIONS,2018,27(11):9-16
刘臣,吉莉,唐莉.基于二分网中心节点识别的产品评论特征-观点词对提取研究.计算机系统应用,2018,27(11):9-16
LIU Chen,JI Li,TANG Li.Research on Product Feature-Opinion Extraction Based on Center Node Recognition in Bipartite Network.COMPUTER SYSTEMS APPLICATIONS,2018,27(11):9-16
