Title :
Webpage clustering - automated classification into jointly classified groups
Author :
Kikuchi, Hiroaki
Author_Institution :
Dept. of Inf. Media Technol., Tokai Univ., Kanagawa, Japan
Abstract :
A directory service for Webpages is widely used over the Internet. Webpages, however, are not always disjointly partitioned into subcategories, i.e., there are some pages to be belonging to multiple groups. To classify pages, conventional clustering algorithms are not adequately applied. This paper proposes a new algorithm of fuzzy clustering specialized for Webpage directory.
Keywords :
Internet; classification; decision trees; fuzzy systems; learning (artificial intelligence); pattern clustering; search engines; Internet; Webpage clustering; Webpage directory service; automated classification; fuzzy clustering; jointly classified groups; Binary trees; Classification tree analysis; Clustering algorithms; Decision trees; Frequency estimation; Partitioning algorithms; Resource description framework; Search engines; Training data; Web pages;
Conference_Titel :
Systems, Man and Cybernetics, 2005 IEEE International Conference on
Print_ISBN :
0-7803-9298-1
DOI :
10.1109/ICSMC.2005.1571574