Bücher von Hujun Yin

IDEAL 2008 was the ninth IDEAL conference to take place; earlier editions were held in Hong Kong, the UK, Australia and Spain. This was the first time, though hopefully not the last time, that it took place in Daejeon, South Korea, during November 2-5, 2008. As the name suggests, the conference attracts researchers who are involved in either data engineering or learning or, increasingly, both. The former topic involves such aspects as data mining (or intelligent knowledge discovery from databases), infor- tion retrieval systems, data warehousing, speech/image/video processing, and mul- media data analysis. There has been a traditional strand of data engineering at IDEAL conferences which has been based on financial data management such as fraud det- tion, portfolio analysis, prediction and so on. This has more recently been joined by a strand devoted to bioinformatics, particularly neuroinformatics and gene expression analysis. Learning is the other major topic for these conferences and this is addressed by - searchers in artificial neural networks, machine learning, evolutionary algorithms, artificial immune systems, ant algorithms, probabilistic modelling, fuzzy systems and agent modelling. The core of all these algorithms is adaptation.

This book constitutes the refereed proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2002, held in Manchester, UK in August 2002.The 89 revised papers presented were carefully reviewed and selected from more than 150 submissions. The book offers topical sections on data mining, knowledge engineering, text and document processing, internet applications, agent technology, autonomous mining, financial engineering, bioinformatics, learning systems, and pattern recognition.

Since its establishment in Hong Kong in 1998,the international Intelligent Data Engineering and Automated Learning (IDEAL) conference has become a r- erence for researchers in both theoretical and practical aspects of learning and information processing, data mining, retrieval and management, bioinformatics and bio-inspired models, agents and hybrid systems and ?nancial engineering. The purpose of IDEAL conferences has been to provide a broad and interd- ciplinary forum for scientists, researchers, and practitioners in these areas from around the world. A special feature of IDEAL conferences is cross-disciplinary exchange of ideas in emerging topics and application in these areas. Data ana- sis and engineering and associated learning paradigms are playing increasingly important roles in an increasing number of applications and ?elds. The mul- disciplinary nature of contemporary research is pushing the boundaries and one of the principal aims of the IDEAL conferences is to promote interactions and collaborations across disciplines. This volume of Lecture Notes in Computer Science contains accepted - pers presented at IDEAL 2006 held at the University of Burgos, Spain, during, September 20-23, 2006. The conference received 557 submissions from over 40 countriesaroundtheworld,whichweresubsequentlyrefereedbytheProgramme Committeeandmanyadditionalreviewers.Afterrigorousreview,170top-quality papers were accepted and included in the proceedings. The acceptance rate was only 30%, which ensured an extremely high-quality standard of the conference. The buoyant number of submitted papers is a clear proof of the vitality and increased importance of the ?elds related to IDEAL, and is also an indication of the rising popularity of the IDEAL conferences.

This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013, held in Hefei, China, in October 2013. The 76 revised full papers presented were carefully reviewed and selected from more than 130 submissions. These papers provided a valuable collection of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modelling, swarm intelligent, multi-objective optimisation, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, including a number of special sessions on emerging topics such as adaptation and learning multi-agent systems, big data, swarm intelligence and data mining, and combining learning and optimisation in intelligent data engineering.