Depth and detours: an essay on visually guided behavior
Vision, brain, and cooperative computation
Microcomputer applications: an empirical look at usage
Information and Management
Playfulness and computers at work
Playfulness and computers at work
Fixed point analysis for recurrent networks
Advances in neural information processing systems 1
Fundamentals of neural networks: architectures, algorithms, and applications
Fundamentals of neural networks: architectures, algorithms, and applications
Measuring system usage: implications for IS theory testing
Management Science
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Doing More Business on the Internet
Doing More Business on the Internet
Testing a causal model of end-user application effectiveness
Journal of Management Information Systems
Testing the determinants of microcomputer usage via a structural equation model
Journal of Management Information Systems - Special section: Navigation in information-intensive environments
Influence of experience on personal computer utilization: testing a conceptual model
Journal of Management Information Systems
Metadata and its impact on libraries: Book Reviews
Journal of the American Society for Information Science and Technology
Weighted order-dependent clustering and visualization of web navigation patterns
Decision Support Systems
Tuning Data Mining Methods for Cost-Sensitive Regression: A Study in Loan Charge-Off Forecasting
Journal of Management Information Systems
Profiling Retail Web Site Functionalities and Conversion Rates: A Cluster Analysis
International Journal of Electronic Commerce
Commercial Internet filters: Perils and opportunities
Decision Support Systems
Information and Management
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Employees' nonwork-related Web surfing behavior results in millions of dollars of expenditure for organizations. This paper proposes the use of a behavior-based artificial intelligence system to profile employee Web usage behavior. Two artificial neural networks (ANN) incorporating genetic algorithm techniques were developed for this purpose. The system was validated with two different data sets. The classification performance of the neural network models was compared to that of a statistical method. The results indicate that one of the ANN models, namely the simple recurrent network, was a superior classifier for this behavior-based problem. In addition, the uncertainty inherent in such classification decisions was examined with a loss matrix, and the holdout samples were reclassified using a loss matrix. The output of this intelligent system can be highly beneficial to managers in designing effective Web management policies.