9783540684152-3540684158-Mining Complex Data: ECML/PKDD 2007 Third International Workshop, MDC 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers (Lecture Notes in Computer Science, 4944)

Mining Complex Data: ECML/PKDD 2007 Third International Workshop, MDC 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers (Lecture Notes in Computer Science, 4944)

ISBN-13: 9783540684152
ISBN-10: 3540684158
Edition: 2008
Author: Zbigniew W. Ras, Shusaku Tsumoto, Djamel A. Zighed
Publication date: 2008
Publisher: Springer
Format: Paperback 275 pages
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Book details

ISBN-13: 9783540684152
ISBN-10: 3540684158
Edition: 2008
Author: Zbigniew W. Ras, Shusaku Tsumoto, Djamel A. Zighed
Publication date: 2008
Publisher: Springer
Format: Paperback 275 pages

Summary

Mining Complex Data: ECML/PKDD 2007 Third International Workshop, MDC 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers (Lecture Notes in Computer Science, 4944) (ISBN-13: 9783540684152 and ISBN-10: 3540684158), written by authors Zbigniew W. Ras, Shusaku Tsumoto, Djamel A. Zighed, was published by Springer in 2008. With an overall rating of 4.2 stars, it's a notable title among other AI & Machine Learning (Computer Science, Data Modeling & Design, Databases & Big Data, Data Mining) books. You can easily purchase or rent Mining Complex Data: ECML/PKDD 2007 Third International Workshop, MDC 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers (Lecture Notes in Computer Science, 4944) (Paperback) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.23.

Description

This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.

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