The Intelligent Data Engineering and Automated Learning (IDEAL) conf- ence series began in 1998 in Hong Kong, when the world started to experience information and data explosion and to demand for better, intelligent meth- ologies and techniques. It has since developed, enjoyed success in recent years, and become a unique annual international forum dedicated to emerging topics and technologies in intelligent data analysis and mining, knowledge discovery, automated learning and agent technology, as well as interdisciplinary appli- tions, especially bioinformatics. These techniques are common and applicable to many ?elds. The multidisciplinary nature of research nowadays is pushing the boundaries and one of the principal aims of the IDEAL conference is to p- mote interactions and collaborations between disciplines, which are bene?cial and bringing fruitful solutions. This volume of Lecture Notes in Computer Science contains accepted papers presented at IDEAL 2004, held in Exeter, UK, August 25-27, 2004. The conf- ence received 272 submissions from all over the world, which were subsequently refereed by the ProgramCommittee. Among them 124 high-quality papers were accepted and included in the proceedings. IDEAL 2004 enjoyed outstanding keynote talks by distinguished guest speakers,Jim Austin, Mark Girolami, Ross King, Lei Xu and Robert Esnouf. This year IDEAL also teamed up with three international journals, namely the International Journal of Neural Systems,the Journal of Mathematical M- elling and Algorithms,and Neural Computing & Applications. Three special issues on Bioinformatics, Learning Algorithms,and Neural Networks & Data Mining, respectively, have been scheduled for selected papers from IDEAL 2004.
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This book constitutes the refereed proceedings of the 5th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2004, held in Exeter, UK, in August 2004. The 124 revised full papers presented were carefully reviewed and selected from 272 submissions. The papers are organized in topical sections on bioinformatics, data mining and knowledge engineering, learning algorithms and systems, financial engineering, and agent technologies.
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