e-book

Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications

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We have all heard of the success story of the discovery of a link between the
mental problems of children and the chemical pollutants in their drinking water.
Similarly, we have heard of the 1854 Broad Street cholera outbreak in London,
and the linking of it to a contaminated public water pump. These are two highprofile
examples of bisociation, the combination of information from two different sources.

This is exactly the focus of the BISON project and this book. Instead of
attempting to keep up with the meaningful annotation of the data floods we are
facing, the BISON group pursued a network-based integration of various types
of data repositories and the development of new ways to analyze and explore the
resulting gigantic information networks. Instead of finding well-defined global or
local patterns they wanted to find domain-bridging associations which are, by
definition, not well defined since they will be especially interesting if they are
sparse and have not been encountered before.

The present volume now collects the highlights of the BISON project. Not
only did the consortium succeed in formalizing the concept of bisociation and
proposing a number of types of bisociation and measures to rank their“bisociativeness,”
but they also developed a series of new algorithms, and extended several
of the existing algorithms, to find bisociation in large bisociative information networks.

From a personal point of view, I was delighted to see that some of our own
work on finding structurally similar pieces in large networks actually fit into that
framework very well: Random walks, and related diffusion-based methods, can
help find correlated nodes in bisociative networks. The concept of bisociative
knowledge discovery formalizes an aspect of data mining that people have been
aware of to some degree but were unable to formally pin down. The present
volume serves as a great basis for future work in this direction.

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Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

New York : Springer Heidelberg Dordrecht London NewYork., 2012

Deskripsi Fisik

x, 300 Hlm.

Bahasa

English

ISBN/ISSN

978-3-642-31830-6

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

MATEMATIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

Lampiran Berkas

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