Finding Topics in News Web Pages by Parameter-free Clustering
Xiang Ji, Neng Gao, Jiwu Jing · 2010
Topic detection is a novel technology which structures news stories into several topics.Present topic detection approaches are mainly based on clustering algorithms such as single pass or agglomerative clustering, and all these algorithms need at least one input parameter.We proposed a novel clustering algorithm which automatically determines the parameters for each corpus.Experimental results show that the parameters derived are close to optimal, and our algorithm has similar accuracy as the UPGMA algorithm which is manually set with optimal parameters.Another advantage of our algorithm is that it runs much faster than the UPGMA algorithm.