Towards automatic clustering of similar pages in web applications
Andrea De Lucia, Michele Risi, Genoveffa Tortora, Giuseppe Scanniello · 2009
In this paper, we propose an automatic approach to group web pages that are similar at the content level. The approach uses the Levenshtein string edit distance and Latent Semantic Indexing to compute page dissimilarity and then groups them using iteratively a Graph-Theoretic clustering algorithm. To automate the clustering process a prototype has been implemented and used to assess the proposed approach on three web sites.