By Topic

Next Generation of Data-Mining Applications

Cover Image Copyright Year: 2005
Author(s): Mehmed Kantardzic; Jozef Zurada
Publisher: Wiley-IEEE Press
Content Type : Books & eBooks
Topics: Communication, Networking & Broadcasting ;  Computing & Processing
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Abstract

Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
Industry and business
Science and engineering
Bioinformatics and biotechnology
Medicine and pharmaceuticals
Web and text-mining
Security
New trends in data-mining technology
And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
New data-mining tools to automate the evaluation and qualification of sales opportunities
The latest tools needed for gene mapping and proteomic data analysis
Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics.

  •   Click to expandTable of Contents

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      Frontmatter

      Page(s): i - xviii
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      The prelims comprise:
      Half Title
      IEEE Press Editorial Board Page
      Title
      Copyright
      Next Generation of Data-Mining Applications
      Contents
      Contributors
      Preface View full abstract»

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      Trends in DataMining Applications: From Research Labs to Fortune 500 Companies

      Page(s): 1 - 13
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      The prelims comprise:
      Introduction
      Characteristics of the Next Generation of Data-Mining Applications
      The Content of the Book View full abstract»

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      Industrial Applications

      Page(s): 15
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

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      Mining Wafer Fabrication: Framework and Challenges

      Page(s): 17 - 40
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Background
      Related Work
      Proposed Framework
      Experimental Study
      Conclusion This chapter contains sections titled:
      References View full abstract»

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      Damage Detection Employing DataMining Techniques

      Page(s): 41 - 55
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Problem Description
      Methodology
      Experimental Results
      Conclusions This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Data Projection Techniques and Their Application in Sensor Array Data Processing

      Page(s): 57 - 77
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Electronic Nose and Sensor Array
      Linear Data Projection
      Nonlinear Data Projection
      Geonlm and Tetrahedral Mapping
      Experiments and Empirical Comparison
      Nonlinear Projections of Electronic Nose Data
      Conclusions This chapter contains sections titled:
      References View full abstract»

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      Business Applications

      Page(s): 79
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

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      An Application of Evolutionary and Neural DataMining Techniques to Customer Relationship Management

      Page(s): 81 - 100
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Application Details
      State-of-the-Art: Application
      Results
      Summary and Outlook This chapter contains sections titled:
      References View full abstract»

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      Sales Opportunity Miner: Data Mining for Automatic Evaluation of Sales Opportunity

      Page(s): 101 - 126
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Problem Formulation
      Related Work
      Sales Opportunity Miner
      Experimental Results and Model Evaluations
      Conclusions This chapter contains sections titled:
      References View full abstract»

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      A Fully Distributed Framework for CostSensitive Data Mining

      Page(s): 127 - 147
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Background on Cost-Sensitive Decision Making
      Distributed Learning Systems
      Experiment
      Discussion
      Related Work
      Conclusions This chapter contains sections titled:
      References View full abstract»

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      Application of Variable Precision Rough Set Approach to Car Driver Assessment

      Page(s): 149 - 164
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Driver History Data
      Variable Precision Rough Set Framework
      Some Results and Interpretations
      Conclusions This chapter contains sections titled:
      Acknowledgment
      References View full abstract»

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      Science and Engineering Applications

      Page(s): 165
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Discovery of Patterns in Earth Science Data Using Data Mining

      Page(s): 167 - 187
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Data Description and Data Sources
      Data Preprocessing
      Clustering
      Association Analysis
      Query Processing
      Other Techniques
      Conclusions This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      An Active Learning Approach to Egeria Densa Detection in Digital Imagery

      Page(s): 189 - 210
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Egeria Detection
      Conventional Approaches
      An Active Learning Approach
      Dual Ensembles for Active Learing
      Empirical Study
      Summary and Conclusion This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Experiences in Mining Data from Computer Simulations

      Page(s): 211 - 232
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      A Brief Introduction to Simulation Data
      Role of Data Mining in Computer Simulations
      Similarity-Based Object Retrieval
      Challenges and Opportunities in Mining Simulation Data
      Summary This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Statistical Modeling of LargeScale Scientific Simulation Data

      Page(s): 233 - 260
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Scientific Simulation Data in Mesh Format
      Statistical Model Generators for Scientific Data
      Future Directions
      Conclusions This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Bioinformatics and Biotechnology Applications

      Page(s): 261
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

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      Data Mining for Gene Mapping

      Page(s): 263 - 293
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Genetic Concepts
      Gene Mapping
      Haplotype Similarity
      Haplotype Clustering
      Discussion This chapter contains sections titled:
      References
      Appendix A: Simulation of Data View full abstract»

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      DataMining Techniques for Microarray Data Analysis

      Page(s): 295 - 329
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Existing Tools
      Improved Tools
      Conclusions This chapter contains sections titled:
      References View full abstract»

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      The Use of Emerging Patterns in the Analysis of Gene Expression Profiles for the Diagnosis and Understanding of Diseases

      Page(s): 331 - 353
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Prediction by Collective Likelihood Based on Emerging Patterns
      Selection of Relevant Genes
      Diagnosis of Disease State or Subtype
      Derivation of Treatment Plan
      Understanding of Molecular Circuit
      Closing Remarks This chapter contains sections titled:
      References View full abstract»

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      Proteomic Data Analysis: Pattern Recognition for Medical Diagnosis and Biomarker Discovery

      Page(s): 355 - 389
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Proteomic Data Analysis
      Biomarker Discovery
      Conclusion This chapter contains sections titled:
      Acknowledgments
      Appendix: Proteomics Methods and Technologies
      References View full abstract»

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      Medical and Pharmaceutical Applications

      Page(s): 391
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Discovering Patterns and Reference Models in the Medical Domain of Isokinetics

      Page(s): 393 - 413
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Related Work
      Preprocessing and Cleaning Patient Isokinetic Records
      Discovering Patterns
      Algorithm to Create Reference Models for Population Groups
      Evaluation
      Conclusions This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Mining the Cystic Fibrosis Data

      Page(s): 415 - 444
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Background and Related Work
      The Cystic Fibrosis Project
      Summary This chapter contains sections titled:
      References View full abstract»

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      Web and Text-Mining Applications

      Page(s): 445
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      On Learning Strategies for TopicSpecific Web Crawling

      Page(s): 447 - 467
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      The Learning Crawler Framework
      Use of Linkage-Based Techniques
      On the Merits of Combining User and Linkage Information for Topical Resource Discovery
      Conclusions and Summary This chapter contains sections titled:
      References View full abstract»

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      On Analyzing Web Log Data: A Parallel SequenceMining Algorithm

      Page(s): 469 - 494
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Related Work
      Click Stream Analysis: An Integrated Solution
      Performance and a Sample Business Analysis
      Future Work and Conclusion This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Interactive Methods for Taxonomy Editing and Validation

      Page(s): 495 - 522
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Gene Rating a Taxonomy
      Viewing the Taxonomy
      Editing the Taxonomy
      Validation
      Text Analysis Versus Structured Information
      Usage Scenario: Interactive Text Mining on Discussion Forum Data
      Conclusions This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Security Applications

      Page(s): 523
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      The Use of DataMining Techniques in Operational Crime Fighting

      Page(s): 525 - 543
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Business Understanding
      Data Understanding
      Data Preparation
      Model Building
      Validation
      Discussion This chapter contains sections titled:
      References View full abstract»

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      Using Data Mining for Intrusion Detection

      Page(s): 545 - 567
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Related Work
      System Architecture and Data Analysis Flow
      Data Format
      Data Mining
      Event-Rate Analysis and Temporal Association
      Clustering
      Application Scenario
      Conclusions This chapter contains sections titled:
      References View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      New Trends in DataMining Technology

      Page(s): 569
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Mining Closed and Maximal Frequent Itemsets

      Page(s): 571 - 598
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Preliminaries
      Existing Approaches for Closed and Maximal Itemset Mining
      Efficient CFI and MFI Mining: Charm and Genmax
      Experimental Results
      Conclusions This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Using Fractals in Data Mining

      Page(s): 599 - 629
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      Intrinsic Dimensionality
      Applications
      Related Work
      Summary This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Genetic Search for Logic Structures in Data

      Page(s): 631 - 661
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      This chapter contains sections titled:
      Introduction
      The Basic Types of Logic Neurons
      Relationships of Fuzzy Neurons with Fuzzy Relational Equations
      A General Topology of the Network
      The Evolutionary Development of the Network
      Interfaces of Fuzzy Networks
      Interpretation Aspects of the Networks
      Experimental Studies
      Conclusions This chapter contains sections titled:
      Acknowledgments
      References View full abstract»

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      Index

      Page(s): 663 - 670
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      About the Editors

      Page(s): 671
      Copyright Year: 2005

      Wiley-IEEE Press eBook Chapters

      Discover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:
      Industry and business
      Science and engineering
      Bioinformatics and biotechnology
      Medicine and pharmaceuticals
      Web and text-mining
      Security
      New trends in data-mining technology
      And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:
      New data-mining tools to automate the evaluation and qualification of sales opportunities
      The latest tools needed for gene mapping and proteomic data analysis
      Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making se nse of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics. View full abstract»