Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
A prediction system for multimedia pre-fetching in Internet
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Research Issues in Web Data Mining
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
Similarity Assessment for Relational CBR
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Data Mining of User Navigation Patterns
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Taylor Series Prediction: A Cache Replacement Policy based on Second-Order Trend Analysis
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 5 - Volume 5
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
WhatNext: A Prediction System for Web Requests using N-gram Sequence Models
WISE '00 Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00)-Volume 1 - Volume 1
Concept Hierarchy Based Text Database Categorization in a Metasearch Engine Environment
WISE '00 Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00)-Volume 1 - Volume 1
Foundations of Soft Case-Based Reasoning
Foundations of Soft Case-Based Reasoning
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In this paper, a fuzzy case based reasoning approach to Web access path prediction is developed and tested. It is based on the assumption that new user's access patterns can be predicted by referencing to the behaviors of similar Web users in the past. This method has three phases. Firstly, a Web case base is constructed from the Web log data. This includes the pre-processing and cleaning of the Web log data so that a suitable format is developed. Secondly, contextual information is extracted from the Web pages, and this information is used to develop a similarity measurement between Web pages. This information is added to the Web case base. Finally, fuzzy association rule mining is used to discover the relationship between the browsing behavior (user navigations) and the Web contents using the Web case base. A set of predictive cases from the Web case base is then selected for the access path prediction. From the experimental evaluation, our approach has demonstrated better prediction accuracy than the existing approaches.