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CO-CLUSTERING BIPARTITE WITH PATTERN PRESERVATION FOR TOPIC EXTRACTION
2008
International journal on artificial intelligence tools
The duality between document and word clustering naturally leads to the consideration of storing the document dataset in a bipartite. With documents and words modeled as vertices on two sides respectively, partitioning such a graph yields a co-clustering of words and documents. The topic of each cluster can then be represented by the top words and documents that have highest within-cluster degrees. However, such claims may fail if top words and documents are selected simply because they are
doi:10.1142/s0218213008003790
fatcat:ydnd3hbd75fypcrn2jcqje42gy