Journal article
Profiling Web usage in the workplace: A behavior-based artificial intelligence approach
Journal of management information systems, v 19(1), pp 243-266
01 Jun 2002
Abstract
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.
Metrics
Details
- Title
- Profiling Web usage in the workplace: A behavior-based artificial intelligence approach
- Creators
- M Anandarajan
- Publication Details
- Journal of management information systems, v 19(1), pp 243-266
- Publisher
- Taylor & Francis
- Number of pages
- 24
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000176356800010
- Scopus ID
- 2-s2.0-0036607546
- Other Identifier
- 991019170611504721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Information Science & Library Science
- Management