Paper Info
Title
Iterative Discovering of User's Preferences Using Web Mining
Abstract
A m ethod of iterative preferences discovering is presented in this paper. It is based on the vector space model and a fuzzy classification of the on-line user's session to precalculated clusters. As a result, the preference vector is created. It measures the user's willingness to see web pages, products in an e-commerce site, masterpieces in a virtual gallery etc. Additionally, formal characteristics of the preference vector are discussed. It is shown, among others, why the fuzzy classification is better than a normal classification for preference vector construction.
Year
Venue
Keywords
2005
IJCSA
fuzzy classification,web mining,e commerce,web pages,vector space model
Field
DocType
Volume
Data mining,Web mining,Web page,Information retrieval,Fuzzy classification,Computer science,Web query classification,Artificial intelligence,Vector space model,Machine learning
Journal
2
Issue
Citations 
PageRank 
2
0
0.34
References 
Authors
7
1
Name
Order
Citations
PageRank
Maciej Kiewra1466.14