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Item Details
Title: LOCAL PATTERN DETECTION
INTERNATIONAL SEMINAR DAGSTUHL CASTLE, GERMANY, APRIL 12-16, 2004, REVISED SELECTED PAPERS
By: Katharina Morik (Editor), Jean-Francois Boulicaut (Editor), Arno Siebes (Editor)
Format: Paperback

List price: £62.99


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ISBN 10: 3540265430
ISBN 13: 9783540265436
Publisher: SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG
Pub. date: 14 July, 2005
Edition: 2005 ed.
Series: Lecture Notes in Computer Science v.3539
Pages: 233
Description: Presents a collection of 13 selected papers originating from the International Seminar on Local Pattern Detection, held in Dagstuhl Castle, Germany in April 2004. This book addresses four main topics, covering frequent set mining, subgroup discovery, the statistical view, and time phenomena.
Synopsis: Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new ?eld knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the ?eld o?ers the opportunity to combine the expertise of di?erent ?elds intoacommonobjective.Moreover,withineach?elddiversemethodshave been developed and justi?ed with respect to di?erent quality criteria. We have toinvestigatehowthesemethods cancontributeto solvingthe problemofKDD. Traditionally, KDD was seeking to ?nd global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to ?nd only the obvious patterns in the data, 1 which domain experts already are aware of .What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new ?eld of local patterns.
Illustrations: biography
Publication: Germany
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Returns: Returnable
Some other items by this author:
ADVANCES IN INTELLIGENT DATA ANALYSIS (PB)
ADVANCES IN INTELLIGENT DATA ANALYSIS XII (PB)
COMPUTATIONAL SUSTAINABILITY (HB)
CONSTRAINT-BASED MINING AND INDUCTIVE DATABASES (PB)
DISCOVERY SCIENCE (PB)
GWAI-87 11TH GERMAN WORKSHOP ON ARTIFICIAL INTELLIGENCE (PB)
INFORMATIK KOMPAKT (PB)
KNOWLEDGE ACQUISITION AND MACHINE LEARNING
KNOWLEDGE ACQUISITION AND MACHINE LEARNING (HB)
KNOWLEDGE DISCOVERY IN DATABASES PKDD 2004 (PB)
KNOWLEDGE DISCOVERY IN INDUCTIVE DATABASES (PB)
KNOWLEDGE DISCOVERY IN INDUCTIVE DATABASES (PB)
KNOWLEDGE REPRESENTATION AND ORGANIZATION IN MACHINE LEARNING (PB)
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES (PB)
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES (PB)
MACHINE LEARNING ECML 2004, (PB)
MAKING ROBOTS SMARTER (HB)
MAKING ROBOTS SMARTER (PB)
PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY (PB)

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