Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
The Strength of Weak Learnability
Machine Learning
Introduction to Grey system theory
The Journal of Grey System
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Original Contribution: The CMAC and a theorem of Kolmogorov
Neural Networks
A sequential algorithm for training text classifiers
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Efficient parallel data mining for association rules
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Training algorithms for linear text classifiers
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
CMAC with general basis functions
Neural Networks
Do-I-Care: a collaborative Web agent
Conference Companion on Human Factors in Computing Systems
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
A system for automatic personalized tracking of scientific literature on the Web
Proceedings of the fourth ACM conference on Digital libraries
Incremental and interactive sequence mining
Proceedings of the eighth international conference on Information and knowledge management
Data mining: concepts and techniques
Data mining: concepts and techniques
ACM SIGKDD Explorations Newsletter
A fast distributed algorithm for mining association rules
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Neural Networks in Computer Intelligence
Neural Networks in Computer Intelligence
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Scalable Algorithms for Association Mining
IEEE Transactions on Knowledge and Data Engineering
Scalable Feature Mining for Sequential Data
IEEE Intelligent Systems
SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
LEARN++: an incremental learning algorithm for multilayer perceptron networks
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Machine learning of user profiles: representational issues
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A self-organizing HCMAC neural-network classifier
IEEE Transactions on Neural Networks
Selection of learning parameters for CMAC-based adaptive critic learning
IEEE Transactions on Neural Networks
Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
Neural Processing Letters
Improved MS_CMAC Neural Networks by Integrating a Simplified UFN Model
Neural Processing Letters
Web Intelligence and Agent Systems
Fuzzy neural Web agents for efficient NBA scouting
Web Intelligence and Agent Systems
Exploring local community structures in large networks
Web Intelligence and Agent Systems
COBRA - mining web for COrporate Brand and Reputation Analysis
Web Intelligence and Agent Systems
Personalization of web-based systems based on computational intelligence modeling
CEA'10 Proceedings of the 4th WSEAS international conference on Computer engineering and applications
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In recent years, information has grown rapidly, especially on the World Wide Web. Also volume of information found by search engines tends to be large, and these documents are not tailored to a user's actual needs and interests. Thus, to offer the personalized service that includes only user interested information becomes increasingly important. Web mining techniques have proven themselves as a very useful tool for mining information of interests on the Web. However, past pioneers' studies have indicated that the main challenges in Web mining are in terms of handling high-dimensional data, achieving incremental learning (or incremental mining), providing scalable mining and parallel and distributed mining algorithms. This study presents a novel self-organizing HCMAC (Hierarchical Cerebellar Model Arithmetic Computer) neural network composed of two-dimensional Weighted Grey CMACs (WGCMAC) capable of handling both higher dimensional classification problems and self-organizing memory structure according to the distribution of training patterns. Moreover, a learning algorithm that can learn incrementally from new added data without forgetting prior knowledge is proposed to train the self-organizing HCMAC neural network. Currently, it is applied to incrementally learn user profiles from user feedback for identifying personalized Web pages. A benchmark dataset of Web pages ratings that contains four topics of user profiles is used to demonstrate the effectiveness of the proposed method. Experimental results show that the self-organizing HCMAC neural network has a good incrementally learning ability and can overcome the problem of enormous memory requirement in the conventional CMAC while it is applied to solve the higher dimensional classification problems. Furthermore, experiments also confirm that the self-organizing HCMAC neural network has a better forecasting ability to identify user interesting Web pages than other well-known classifiers do.