Today, fuzzy methods are of common use as they provide tools to handle data sets in a relevant, robust, and interpretable way, making it possible to cope with both imprecision and uncertainties. Scalable Fuzzy Algorithms for Data Management and Analysis: Methods and Design presents up-to-date techniques for addressing data management problems with logic and memory use. This critical mass of the most sought after findings covers a wide scope of research areas from both a theoretical and experimental point of view.
Author(s): Anne Laurent, Marie-Jeanne Lesot
Edition: 1
Year: 2009
Language: English
Pages: 444
Title
......Page 2
List of Reviewers......Page 4
Table of Contents......Page 5
Detailed Table of Contents......Page 8
Foreword......Page 14
Preface......Page 16
Acknowledgment......Page 22
Electronic Hardware for
Fuzzy Computation......Page 24
Scaling Fuzzy Models......Page 54
Using Fuzzy Song Sets
in Music Warehouses......Page 77
Mining Association Rules
from Fuzzy DataCubes......Page 107
Scalable Reasoning
with Tractable Fuzzy
Ontology Languages......Page 153
A Random Set and Prototype
Theory Model of Linguistic
Query Evaluation......Page 182
A Flexible Language
for Exploring Clustered
Search Results......Page 202
Linguistic Data Summarization......Page 237
Human Focused Summarizing
Statistics Using OWA Operators......Page 261
(Approximate) Frequent Item
Set Mining Made Simple with
a Split and Merge Algorithm......Page 277
Fuzzy Association Rules
to Summarise Multiple
Taxonomies in Large Databases......Page 296
Fuzzy Cluster Analysis
of Larger Data Sets......Page 325
Fuzzy Clustering with
Repulsive Prototypes......Page 355
Early Warning from Car
Warranty Data using a
Fuzzy Logic Technique......Page 370
High Scale Fuzzy Video Mining......Page 388
Fuzzy Clustering
of Large Relational
Bioinformatics Datasets......Page 402
Compilation of References......Page 423
About the Contributors......Page 452
Index......Page 461
