Semantic-based Web Page Clustering System Using Enhanced Agglomerative Algorithm
Ei Ei Moe, Hnin Hnin Htun, Aye Mon Yi · 2018
Web page clustering is an important role for providing intuitive navigation and browsing mechanism. This clustering process provides a structure for organizing large bodies of text for efficient browsing and searching. Because of the polysemous and synonyms problems, keyword-based web page clustering system can eliminate the performance of browsing mechanism. So, this system proposes as the semantic based web page clustering system. For semantic analysis, word sense disambiguation (WSD) process is used to get the best senses to be used as features in the clustering process. By using semantic features in each web page, this system clusters each web page. For clustering, this system uses the enhanced Agglomerative hierarchical clustering algorithm which can produce each cluster according to the user desired cluster number. Furthermore, this algorithm can allow the user to view cluster content as the hierarchical level. Finally, the proposed system points out the semantic that is effective for web page clustering.