Using symbolic objects to cluster web documents

Web Clustering is useful for several activities in the WWW, from automatically building web directories to improve retrieval performance. Nevertheless, due to the huge size of the web, a linear mechanism must be employed to cluster web documents. The k-means is one classic algorithm used in this problem. We present a variant of the vector model to be used with the k-means algorithm. Our representation uses symbolic objects for clustering web documents. Some experiments were done with positive results and future work is optimistic. Categories and Subject Descriptors I.7.m [Document and Text Processing]: Miscellaneous; D.2.8 [Software Engineering]: Metrics--performance measures General Terms Algorithms Keywords Symbolic Data Analysis, Web Clustering

• Type: Conference
• Year: 2006
• Where: WWW
• Authors: Esteban Meneses, Oldemar Rodríguez-Rojas
• Keywords: Internet Technology, Keywords Symbolic Data, Web Clustering, Web Documents, WWW 2006