Graphical Models_Representations for Learning, Reasoning and Data Mining,Second Edition
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Authors(Editors):
        Christian Borgelt
        Matthias Steinbrecher
        Rudolf Kruse
Publisher: Wiley
Pub Date: 2009
Pages: 397
ISBN: 978-0-470-72210-7

Preface
Although the origins of graphical models can be traced back to the beginning
of the 20th century, they have become truly popular only since the mideighties,
when several researchers started to use Bayesian networks in expert
systems. But as soon as this start was made, the interest in graphical models
grew rapidly and is still growing to this day. The reason is that graphical
models, due to their explicit and sound treatment of (conditional) dependences
and independences, proved to be clearly superior to naive approaches like
certainty factors attached to if-then-rules, which had been tried earlier.
Data Mining, also called Knowledge Discovery in Databases, is a another
relatively young area of research, which has emerged in response to the flood
of data we are faced with nowadays. It has taken up the challenge to develop
techniques that can help humans discover useful patterns in their data.
In industrial applications patterns found with these methods can often be
exploited to improve products and processes and to increase turnover.
This book is positioned at the boundary between these two highly important
research areas, because it focuses on learning graphical models from
data, thus exploiting the recognized advantages of graphical models for learning
and data analysis. Its special feature is that it is not restricted to probabilistic
models like Bayesian and Markov networks. It also explores relational
graphical models, which provide excellent didactical means to explain the
ideas underlying graphical models. In addition, possibilistic graphical models
are studied, which are worth considering if the data to analyze contains imprecise
information in the form of sets of alternatives instead of unique values.
Looking back, this book has become longer than originally intended. However,
although it is true that, as C.F. von Weizs¨acker remarked in a lecture,
anything ultimately understood can be said briefly, it is also evident that
anything said too briefly is likely to be incomprehensible to anyone who has
not yet understood completely. Since our main aim was comprehensibility, we
hope that a reader is remunerated for the length of this book by an exposition
that is clear and self-contained and thus easy to read.
Christian Borgelt, Matthias Steinbrecher, Rudolf Kruse
Oviedo and Magdeburg, March 2009



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