Scalable Fuzzy Algorithms for Data Management and Analysis: Methods and Design, 1st Edition

  • Anne Laurent
  • Published By:
  • ISBN-10: 1605668591
  • ISBN-13: 9781605668598
  • DDC: 006.3
  • Grade Level Range: College Freshman - College Senior
  • 305 Pages | eBook
  • Original Copyright 2009 | Published/Released March 2010
  • This publication's content originally published in print form: 2009

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About

Overview

"Scalable Fuzzy Algorithms for Data Management and Analysis: Methods and Design" presents innovative, cutting-edge fuzzy techniques that highlight the relevance of fuzziness for huge data sets in the perspective of scalability issues, from both a theoretical and experimental point of view. It covers a wide scope of research areas including data representation, structuring and querying as well as information retrieval and data mining. It encompasses different forms of databases, including data warehouses, data cubes, tabular or relational data, and many applications among which music warehouses, video mining, bioinformatics, semantic web and data streams.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
List of Reviewers.
Table of Contents.
Detailed Table of Contents.
Foreword.
Preface.
Acknowledgment.
1: Introductory Chapters.
2: Electronic Hardware for Fuzzy Computation.
3: Scaling Fuzzy Models.
4: Databases and Queries.
5: Using Fuzzy Song Sets in Music Warehouses.
6: Mining Association Rules from Fuzzy Datacubes.
7: Scalable Reasoning with Tractable Fuzzy Ontology Languages.
8: A Random Set and Prototype Theory Model of Linguistic Query Evaluation.
9: A Flexible Language for Exploring Clustered Search Results.
10: Summarization.
11: Linguistic Data Summarization: A High Scalability through the Use of Natural Language?.
12: Human Focused Summarizing Statistics Using OWA Operators.
13: (Approximate) Frequent Item Set Mining Made Simple with a Split and Merge Algorithm.
14: Fuzzy Association Rules to Summarise Multiple Taxonomies in Large Databases.
15: Fuzzy Cluster Analysis of Larger Data Sets.
16: Fuzzy Clustering with Repulsive Prototypes.
17: Real-World Challenges.
18: Early Warning from Car Warranty Data Using a Fuzzy Logic Technique.
19: High Scale Fuzzy Video Mining.
20: Fuzzy Clustering of Large Relational Bioinformatics Datasets.
Compilation of References.
About the Contributors.
Index.