Topic discovery based on text clustering techniques
Zhen Yan-xia · Jisuanji gongcheng yu sheji · 2008
A topic discovery system aimed to reveal the implicit knowledge present in streams is presented.This knowledge is expressed as a hierarchy of topic/subtopics,where each topic contains the set of related documents and summary extracted from these documents.It is useful to browse and select topics of interest from the generated hierarchies.The method consists of a new incremental hierarchical clustering algorithm,which combines both partitional and agglomerative approaches.Experimental results demonstrate its effectiveness not only as a topic detection system,but also as a classification and summarization tool.