Title :
NaviSOM: Automatic Construction of Navigational Structure for Web Pages using Self-organizing Maps
Author :
Yang, Hsin-Chang ; Lee, Chung-Hong
Author_Institution :
Chang Jung Univ., Tainan
Abstract :
One major approach for information finding in the WWW is to navigate through some web directories and browse them for the goal pages. However, such directories are generally constructed manually and have disadvantages of narrow coverage and inconsistency. In this work, we propose NaviSOM, a machine learning approach to automatically construct a navigational structure for the WWW. A self-organizing map is constructed to train the web pages and obtain two feature maps, which reveal the relationships among web pages and thematic keywords respectively. We then use these maps to develop a structure that may assist the users finding the information they need. We used a small set of web pages in the experiments and obtained promising result.
Keywords :
Web sites; learning (artificial intelligence); self-organising feature maps; NaviSOM; WWW; Web pages; information finding; machine learning approach; navigational structure; self-organizing maps; thematic keywords; Humans; Machine learning; Navigation; Portals; Search engines; Self organizing feature maps; Standards development; Text mining; Web pages; World Wide Web;
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
DOI :
10.1109/IJCNN.2006.246793