A massively parallel architecture for a self-organizing neural pattern recognition machine
Computer Vision, Graphics, and Image Processing
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Web prefetching between low-bandwidth clients and proxies: potential and performance
SIGMETRICS '99 Proceedings of the 1999 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Data mining and the Web: past, present and future
Proceedings of the 2nd international workshop on Web information and data management
Web user clustering from access log using belief function
Proceedings of the 1st international conference on Knowledge capture
Faster Web Page Allocation with Neural Networks
IEEE Internet Computing
Clustering the Users of Large Web Sites into Communities
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Alleviating the latency and bandwidth problems in WWW browsing
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
The bipartite clique: a topological paradigm for WWWeb user search customization
Proceedings of the 43rd annual Southeast regional conference - Volume 1
Data & Knowledge Engineering
Algorithms for clustering clickstream data
Information Processing Letters
A web page usage prediction scheme using sequence indexing and clustering techniques
Data & Knowledge Engineering
A web-page usage prediction scheme using weighted suffix trees
SPIRE'07 Proceedings of the 14th international conference on String processing and information retrieval
Prediction of yeast protein-protein interactions by neural feature association rule
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Prediction of protein interaction with neural network-based feature association rule mining
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
A novel ant-based clustering algorithm using the kernel method
Information Sciences: an International Journal
Classified ranking of semantic content filtered output using self-organizing neural networks
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Neural feature association rule mining for protein interaction prediction
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Applying modified fuzzy neural network to customer classification of e-business
WINE'05 Proceedings of the First international conference on Internet and Network Economics
Application of a modified fuzzy ART network to user classification for internet content provider
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
Adaptive neural network-based clustering of yeast protein: protein interactions
CIT'04 Proceedings of the 7th international conference on Intelligent Information Technology
Short Survey: A taxonomy of web prediction algorithms
Expert Systems with Applications: An International Journal
A user classification for internet content provider based modified fuzzy neural network
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
A novel ant-based clustering algorithm using Renyi entropy
Applied Soft Computing
| Hi-index | 4.10 |
Web server access logs contain substantial data about user access patterns, which can enhance the degree of personalization that a Web site offers. Restructuring a site to individual user interests increases the computation at the server to an impractical degree, but organizing according to user groups can improve perceived performance. An unsupervised clustering algorithm based on adaptive resonance theory adapts to changes in users' access patterns over time without losing earlier information. The algorithm outperformed the traditional k-means clustering algorithm in terms of intracluster distances. A prefetching application based on the algorithm achieved a hit accuracy rate for Web site page requests ranging from 82.05 to 97.78 percent.