IDEAL 2004

Topological Tree for Web Organisation, Discovery and Exploration

By Richard Freeman and Hujun Yin

Abstract

In this paper we focus on the organisation of web contents, which allows efficient browsing, searching and discovery. We propose a method that dynamically creates such a structure called Topological Tree. The tree is generated using an algorithm called Automated Topological Tree Organiser, which uses a set of hierarchically organised self-organising growing chains. Each chain fully adapts to a specific topic, where its number of subtopics is determined using entropy-based validation and cluster tendency schemes. The Topological Tree adapts to the natural underlying structure at each level in the hierarchy. The topology in the chains also relates close topics together, thus can be exploited to reduce the time needed for search and navigation. This method can be used to generate a web portal or directory where browsing and user comprehension are improved.

Keywords

Document categorization, taxonomy generation, information retrieval, content management, topic hierarchy, self-organizing maps, topological tree structure, hierarchical clustering, Bayesian Information Criterion
neural networks

Bibliographic Details

@inproceedings{freemanIdeal04,
   Author = {Freeman, Richard and Yin, Hujun},
   Title = {Self-organising maps for hierarchical tree view document clustering using 
   contextual information},
   BookTitle = {Intelligent Data Engineering and Automated Learning-IDEAL 2004. 
   Fifth International Conference, 25-27 Aug. 2004},
   Series = {Lecture Notes in Computer Science Vol.3177},
   Address= {Exeter, UK},
   Publisher = {Springer-Verlag},
   Pages = {478-484},
   Year = {2004} }
}