Graph based Version of AHC Algorithm for Document Clustering

This article proposes the modified AHC (Agglomerative HierarchicalClustering) algorithm which clusters graphs, instead of numericalvectors, as the approach to the text clustering. The graph is moregraphical for representing a word and the synergy effect between thetext clustering and the word clustering is expected by combiningthem with each other. In this research, we propose the similaritymetric between two graphs representing texts, and modify the AHCalgorithm by adopting the proposed similarity metric as the approachto the text clustering. The proposed AHC algorithm is empiricallyvalidated as the better approach in clustering texts in newsarticles and opinions. In this article, a text is encoded into aweighted and undirected graph and it is represented into a list ofedges.