Local Pattern Detection : International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers

Katharina Morik

ISBN 10: 3540265430 / ISBN 13: 9783540265436

Published by Springer Berlin Heidelberg, 2005

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783540265436

Bibliographic Details

• Title: Local Pattern Detection : International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
• Publisher: Springer Berlin Heidelberg
• Publication Date: 2005
• Language: English
• ISBN 10: 3540265430
• ISBN 13: 9783540265436
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 14D millimeters 235 millimeters width by 155 millimeters height by 14 millimeters depth
• Weight: 382 grams

About this title

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.

Product Description

Local Pattern Detection 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.