Web Mining by Automatically Organizing Web Pages into Categories - Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications - page 214

Chapter XII
Web Mining by Automatically
Organizing Web Pages into
Categories
Ben Choi
Louisiana Tech University, USA
Zhongmei Yao
Louisiana Tech University, USA
aBstract
Web mining aims for searching, organizing, and extracting information on the Web and search engines
focus on searching. The next stage of Web mining is the organization of Web contents, which will then
facilitate the extraction of useful information from the Web. This chapter will focus on organizing Web
contents. Since a majority of Web contents are stored in the form of Web pages, this chapter will focus
on techniques for automatically organizing Web pages into categories. Various artificial intelligence
techniques have been used; however the most successful ones are classification and clustering. This
chapter will focus on clustering. Clustering is well suited for Web mining by automatically organizing
Web pages into categories each of which contain Web pages having similar contents. However, one prob-
lem in clustering is the lack of general methods to automatically determine the number of categories or
clusters. For the Web domain, until now there is no such a method suitable for Web page clustering. To
address this problem, this chapter describes a method to discover a constant factor that characterizes
the Web domain and proposes a new method for automatically determining the number of clusters in
Web page datasets. This chapter also proposes a new bi-directional hierarchical clustering algorithm,
which arranges individual Web pages into clusters and then arranges the clusters into larger clusters
and so on until the average inter-cluster similarity approaches the constant factor. Having the constant
factor together with the algorithm, this chapter provides a new clustering system suitable for mining
the Web.