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Data mining

Most popular at the top

  • The Text Mining Handbookby Ronen Feldman; James Sanger

    Cambridge University Press 2006; US$ 76.00

    Covers text mining and link detection algorithms, pre-processing techniques, knowledge representation, visualization and applications. more...

  • Data Mining Using SAS Enterprise Minerby Randall Matignon

    Wiley 2007; US$ 130.00

    Randall Matignon, MS , is Senior Clinical SAS / Microsoft Office VBA Programmer for Amgen, Inc. in San Francisco, California. He has over twenty years of experience as a statistical programmer and applications developer in the pharmaceutical, healthcare, and biotechnology industries, and he has a broad knowledge of several programming languages, including... more...

  • Advanced Techniques in Knowledge Discovery and Data Miningby Nikhil R. Pal; L.C. Jain

    Springer 2007; US$ 179.00

    Presents advanced tools and techniques available for data and web mining strategies with chapters written by leading world experts. This book provides practicing engineers and scientists with case studies using approaches for data and web mining strategies, and research students with in-depth tutorials on the topics covered. more...

  • Adaptive Web Sitesby J.D. Velásquez; V. Palade

    IOS Press 2008; US$ 161.00

    This book can be presented in two different ways; introducing a particular methodology to build adaptive Web sites and; presenting the main concepts behind Web mining and then applying them to adaptive Web sites. In this case, adaptive Web sites is the case study to exemplify the tools introduced in the text. The authors start by introducing the Web... more...

  • Symbolic Data Analysis and the SODAS Softwareby Edwin Diday; Monique Noirhomme-Fraiture

    Wiley 2008; US$ 199.00

    Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard statistical methods do not have the power or flexibility to make sense of very large datasets, and symbolic data analysis techniques have been developed in order to extract knowledge from such data. Symbolic data methods differ... more...

  • Mathematical Tools for Data Miningby Dan A. Simovici; Chabane Djeraba

    Springer 2008; US$ 209.00

    The maturing of the field of data mining has brought about an increased level of mathematical sophistication. Such disciplines like topology, combinatorics, partially ordered sets and their associated algebraic structures (lattices and Boolean algebras), and metric spaces are increasingly applied in data mining research. This book presents these mathematical... more...

  • Literature-based Discoveryby Peter Bruza; Marc Weeber

    Springer 2008; US$ 159.00

    Literature-based discovery (LBD) is an inherently multi-disciplinary enterprise where collaborations between the information and biomedical sciences are readily encountered. This volume intends to plant a flag in the ground and inspire researchers to the LBD challenge. more...

  • Data Mining in Grid Computing Environmentsby Werner Dubitzky

    Wiley 2008; US$ 149.95

    Based around eleven international real life case studies and including contributions from leading experts in the field this groundbreaking book explores the need for the grid-enabling of data mining applications and provides a comprehensive study of the technology, techniques and management skills necessary to create them. This book provides a simultaneous... more...

  • Privacy-Preserving Data Miningby Charu C. Aggarwal; Philip S. Yu

    Springer 2008; US$ 209.00

    Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes. Privacy-Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a... more...

  • Cluster Analysis for Data Mining and System Identificationby János Abonyi; Balázs Feil

    Springer 2007; US$ 139.00

    Identifies fuzzy cluster analysis as a good approach to solving complex data mining and system identification problems. This work illustrates how advanced fuzzy clustering algorithms can be used for partitioning of the data, and also for visualization, regression, classification and time-series analysis. more...