Database Theory and Application, Bio-Science and Bio-Technology
Database Theory and Application, Bio-Science and Bio-Technology

Author: Tai-hoon Kim

Publisher: Springer

Published: 2011-12-02

Total Pages: 208

ISBN-13: 364227157X

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This book comprises selected papers of the International Conferences, DTA and BSBT 2011, held as Part of the Future Generation Information Technology Conference, FGIT 2011, in Conjunction with GDC 2011, Jeju Island, Korea, in December 2011. The papers presented were carefully reviewed and selected from numerous submissions and focuse on the various aspects of database theory and application, and bio-science and bio-technology.

Legal Knowledge Representation:Automatic Text Analysis in Public International and European Law
Legal Knowledge Representation:Automatic Text Analysis in Public International and European Law

Author: Erich Schweighofer

Publisher: Kluwer Law International B.V.

Published: 1999-10-19

Total Pages: 448

ISBN-13: 9041111484

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This volume is a presentation of all methods of legal knowledge representation from the point of view of jurisprudence as well as computer science. A new method of automatic analysis of legal texts is presented in four case studies. Law is seen as an information system with legally formalised information processes. The achieved coverage of legal knowledge in information retrieval systems has to be followed by the next step: conceptual indexing and automatic analysis of texts. Existing approaches of automatic knowledge representations do not have a proper link to the legal language in information systems. The concept-based model for semi-automatic analysis of legal texts provides this necessary connection. The knowledge base of descriptors, context-sensitive rules and meta-rules formalises properly all important passages in the text corpora for automatic analysis. Statistics and self-organising maps give assistance in knowledge acquisition. The result of the analysis is organised with automatically generated hypertext links. Four case studies show the huge potential but also some drawbacks of this approach.

Energy Minimization Methods in Computer Vision and Pattern Recognition
Energy Minimization Methods in Computer Vision and Pattern Recognition

Author: Marcello Pelillo

Publisher: Springer Science & Business Media

Published: 1997-04-29

Total Pages: 568

ISBN-13: 9783540629092

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This book constitutes the refereed proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR'97, held in Venice, Italy, in May 1997. The book presents 29 revised full papers selected from a total of 62 submissions. Also included are four full invited papers and a keynote paper by leading researchers. The volume is organized in sections on contours and deformable models, Markov random fields, deterministic methods, object recognition, evolutionary search, structural models, and applications. The volume is the first comprehensive documentation of the application of energy minimization techniques in the areas of compiler vision and pattern recognition.

Computational Models of Learning
Computational Models of Learning

Author: Leonard Bolc

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 214

ISBN-13: 364282742X

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In recent years, machine learning has emerged as a significant area of research in artificial intelligence and cognitive science. At present, research in the field is being intensified from both the point of view of theory and of implementation, and the results are being introduced in practice. Machine learning has recently become the subject of interest of many young and talented scientists whose bold ideas have greatly contributed to the broadening of knowledge in this rapidly developing field of science. This situation has manifested itself in an increasing number of valuable contributions to scientific journals. However, such papers are necessarily compact descriptions of research problems. Computational Models of Learning supplements these contributions and is a collection of more extensive essays. These essays provide the reader with an increased knowledge of carefully selected problems of machine learning.