Local Pattern Detection: International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers - Lecture Notes in Computer Science - Katharina Morik - Livros - Springer-Verlag Berlin and Heidelberg Gm - 9783540265436 - 14 de julho de 2005
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Katharina Morik
Local Pattern Detection: International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers - Lecture Notes in Computer Science

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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.

Marc Notes: International Seminar on Local Pattern Detection--P. [4] of cover.; Includes bibliographical references and author index.; Also issued online. Table of Contents: Pushing Constraints to Detect Local Patterns.- From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms.- Pattern Discovery Tools for Detecting Cheating in Student Coursework.- Local Pattern Detection and Clustering.- Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery.- Visualizing Very Large Graphs Using Clustering Neighborhoods.- Features for Learning Local Patterns in Time-Stamped Data.- Boolean Property Encoding for Local Set Pattern Discovery: An Application to Gene Expression Data Analysis.- Local Pattern Discovery in Array-CGH Data.- Learning with Local Models.- Knowledge-Based Sampling for Subgroup Discovery.- Temporal Evolution and Local Patterns.- Undirected Exception Rule Discovery as Local Pattern Detection.- From Local to Global Analysis of Music Time Series. Publisher Marketing: 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

Mídia Livros     Paperback Book   (Livro de capa flexível e brochura)
Lançado 14 de julho de 2005
ISBN13 9783540265436
Editoras Springer-Verlag Berlin and Heidelberg Gm
Páginas 248
Dimensões 156 × 234 × 13 mm   ·   353 g
Idioma Alemão  

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