E-Commerce and Intelligent Methods

by Javier Segovia (Editor), Piotr S. Szczepaniak (Editor), Marian Niedzwiedzinski (Editor)

Overview

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 environments 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 conferences, 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 researchers 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 different backgrounds.

Product Details

ISBN-13:	9783790825145
Publisher:	Physica-Verlag HD
Publication date:	12/15/2010
Series:	Studies in Fuzziness and Soft Computing , #105
Edition description:	Softcover reprint of the original 1st ed. 2002
Pages:	367
Product dimensions:	6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

1. Foundations of Electronic Commerce.- Barriers to Global Electronic Commerce.- Foundations of Electronic Data Interchange.- Some Legal Aspects of Electronic Commerce.- 2. Neural Networks.- Competitive Neural Networks for Customer Choice Models.- CRM in e-Business: a Client’s Life Cycle Model Based on a Neural Network.- Customer Relationship Management Systems: The Application of Fuzzy ART Neural Network.- Characterizing and Segmenting the Online Customer Market Using Neural Netwoks.- Data Mining for Diverse E-Commerce Applications.- Extreme Sample Classification and Credit Card Fraud Detection.- 3. Evolutionary Programming.- A Review of Evolutionary Algorithms for E-Commerce.- Artificial Adaptive Market Traders Based in Genetic Algorithms for a Sk Market Simulator.- Data Mining in Marketing Using Bayesian Networks and Evolutionary Programming.- Improving User Profiles for E-Commerce by Genetic Algorithms.- 4. Fuzzy Logic.- Automatic Web User Profiling and Personalization Using Robust Fuzzy Relational Clustering.- Fuzzy Quantifiable Trust in Secure E-Commerce.- Fuzzy Similarity in E-Commerce Domains.- 5. CBR and Agents.- Agencies of Agents for Logistic Applications.- Intelligent Customer Support for Product Selection with Case-Based Reasoning.- Mobile Agent Based Auctionlike Negotiation in Internet Retail Commerce.- Author Index.