Description
Today, fuzzy methods provide tools to handle data sets in relevant,
robust and interpretable ways, making it possible to model and exploit
imprecision and uncertainty in data modeling and data mining.
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.