According to the requirement of online public opinion analysis, this paper builds an online public opinion hotspot detection and analysis system based on document clustering. It builds vector space model by abstracting document features from sample Web pages, and get the hot-spot cluster by OPTICS algorithm. According the vector of hot-spot cluster, the Web pages are clustered for the second time. At last, it gets the time evolution mode about the public opinion to afford decision support for specific field,and improves the quality of page correlation and analyze the public opinion more accurately.
王伟,许鑫. 基于聚类的网络舆情热点发现及分析*[J]. 现代图书情报技术, 2009, 3(3): 74-79.
Wang Wei,Xu Xin. Online Public Opinion Hotspot Detection and Analysis Based on Document Clustering. New Technology of Library and Information Service, 2009, 3(3): 74-79.