Data mining: concepts and techniques
Data mining: concepts and techniques
Analyzing clickstreams using subsessions
Proceedings of the 3rd ACM international workshop on Data warehousing and OLAP
A fine grained heuristic to capture web navigation patterns
ACM SIGKDD Explorations Newsletter
Feature Matrices: A Model for Efficient and Anonymous Web Usage Mining
EC-Web 2001 Proceedings of the Second International Conference on Electronic Commerce and Web Technologies
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
A rough-fuzzy document grading system for customized text information retrieval
Information Processing and Management: an International Journal
A framework to integrate business goals in web usage mining
AWIC'03 Proceedings of the 1st international Atlantic web intelligence conference on Advances in web intelligence
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Due to the competitive environment in which we are moving, web sites need to be very attractive for visitors. In this paper we propose an approach to analyze and determine the level of affability of a web site that tends to secure user's satisfaction, based on both the kind of page and the kind of user. We propose a granular approach based on the idea that a page can be considered as a set of features or factors. In fact, each of them can be perceived at different granularity levels. The proposed approach makes it possible to estimate a measure of affinity of a user for each level of each particular factor. On any particular page, each factor takes a certain level or value. The global measure of affinity for a certain page will be calculated jointly considering the levels or values that the attributes of this particular page have for each design factor.