MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION by Petra Perner (Editor), Atsushi Imiya (Editor) ( 9783540269236 )

Item Details

Title:

MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION
4TH INTERNATIONAL CONFERENCE, MLDM 2005, LEIPZIG, GERMANY, JULY 9-11, 2005, PROCEEDINGS

By:

Petra Perner (Editor), Atsushi Imiya (Editor)

Format:

Paperback

List price:	£117.00
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ISBN 10:

3540269231

ISBN 13:

9783540269236

Publisher:

SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG

Pub. date:

8 July, 2005

Series:

Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence v.3587

Pages:

698

Description:

Constitutes the proceedings of the 4th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2005, held in Leipzig, Germany, in July 2005. The papers are organized in topical sections on classification and model estimation, neural methods, subspace methods, and more.

Synopsis:

We met again in front of the statue of Gottfried Wilhelm von Leibniz in the city of Leipzig. Leibniz, a famous son of Leipzig, planned automatic logical inference using symbolic computation, aimed to collate all human knowledge. Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled "machine learning" and "data mining", whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems.We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.

Illustrations:

biography

Publication:

Germany

Imprint:

Springer-Verlag Berlin and Heidelberg GmbH & Co. K

Returns:

Returnable

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