E-Commerce and Intelligent Methods

Front Cover
Javier Segovia, Piotr S. Szczepaniak, Marian Niedzwiedzinski
Springer Science & Business Media, Aug 6, 2002 - Computers - 367 pages
This book covers significant recent developments in the field of Intelligent Meth ods applied to eCommerce. The Intelligent Methods considered are mainly Soft Computing Methods that include fuzzy sets, rough sets, neural networks, evolutionary computations, probabilistic and evidential reasoning, multivalued logic, and related fields. There is not doubt about the relevance of eCommerce in our daily environ ments and in the work carried out at many research centers throughout the world. The application of AI to Commerce is growing as fast as the computers and net works are being integrated in all business and commerce aspects. We felt that it was time to sit down and see how was the impact into that field of low-level AI, i.e. softcomputing. We found many scattered contributions disseminated in con ferences, workshops, journal, books or even technical reports, but nothing like a common framework that could serve as a basis for further research, comparison or even prototyping for a direct transfer to the industry. We felt then the need to set up a reference point, a book like this. We planned this book as a recompilation of the newest developments of re searchers who already made some contribution into the field. The authors were se lected based on the originality and quality of their work and its relevance to the field. Authors came from prestigious universities and research centers with differ ent backgrounds.
 

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Contents

Barriers to Global Electronic Commerce
3
Foundations of Electronic Data Interchange
13
Some Legal Aspects of Electronic Commerce
19
Neural Networks
39
Competitive Neural Networks for Customer Choice Models
41
a Clients Life Cycle Model Based on a Neural Network
61
The Application of Fuzzy ART Neural Network
78
Characterizing and Segmenting the Online Customer Market Using Neural Networks
101
Data Mining in Marketing Using Bayesian Networks and Evolutionary Programming
198
Improving User Profiles for ECommerce by Genetic Algorithms
215
Fuzzy Logic
231
Automatic Web User Profiling and Personalization Using Robust Fuzzy Relational Clustering
233
Fuzzy Quantifiable Trust in Secure ECommerce
262
Fuzzy Similarity in ECommerce Domains
281
CBR and Agents
291
Agencies of Agents for Logistic Applications
293

Data Mining for Diverse ECommerce Applications
120
Extreme Sample Classification and Credit Card Fraud Detection
136
Evolutionary Programming
157
A Review of Evolutionary Algorithms for ECommerce
159
Artificial Adaptive Market Traders Based in Genetic Algorithms for a Stock Market Simulator
180
Intelligent Customer Support for Product Selection with CaseBased Reasoning
322
Mobile Agent Based Auctionlike Negotiation in Internet Retail Commerce
342
Subject Index
363
Author Index
Copyright

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