Discovering relationships between topics of conferences by filtering, extracting and clustering
Tsunenori Mine, Shan Lu, Makoto Amamiya · 2004
This paper presents a text mining system that obtains the relationships between the topics of international conferences. The system at first gathers Web pages related to the query 'call for paper' with a search engine and filters out pages irrelevant to the query with SVMs. Next it extracts the topics of conferences and clusters them. Each cluster embodies the relationships between topics and between topics and conferences. The clustered topics are shown through an Explorer-like graphical user interface. The preliminary experimental results promise that the method works not only for obtaining the relationship between topics of conferences, but also for discovering the relationship between any information entities users are interested in.