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This book presents a comprehensive and systematic introduction to
transforming process-oriented data into information about the
underlying business process, which is essential for all kinds of
decision-making. To that end, the authors develop step-by-step
models and analytical tools for obtaining high-quality data
structured in such a way that complex analytical tools can be
applied. The main emphasis is on process mining and data mining
techniques and the combination of these methods for
process-oriented data. After a general introduction to the business
intelligence (BI) process and its constituent tasks in chapter 1,
chapter 2 discusses different approaches to modeling in BI
applications. Chapter 3 is an overview and provides details of data
provisioning, including a section on big data. Chapter 4 tackles
data description, visualization, and reporting. Chapter 5
introduces data mining techniques for cross-sectional data.
Different techniques for the analysis of temporal data are then
detailed in Chapter 6. Subsequently, chapter 7 explains techniques
for the analysis of process data, followed by the introduction of
analysis techniques for multiple BI perspectives in chapter 8. The
book closes with a summary and discussion in chapter 9. Throughout
the book, (mostly open source) tools are recommended, described and
applied; a more detailed survey on tools can be found in the
appendix, and a detailed code for the solutions together with
instructions on how to install the software used can be found on
the accompanying website. Also, all concepts presented are
illustrated and selected examples and exercises are provided. The
book is suitable for graduate students in computer science, and the
dedicated website with examples and solutions makes the book ideal
as a textbook for a first course in business intelligence in
computer science or business information systems. Additionally,
practitioners and industrial developers who are interested in the
concepts behind business intelligence will benefit from the clear
explanations and many examples.
This book presents a comprehensive and systematic introduction to
transforming process-oriented data into information about the
underlying business process, which is essential for all kinds of
decision-making. To that end, the authors develop step-by-step
models and analytical tools for obtaining high-quality data
structured in such a way that complex analytical tools can be
applied. The main emphasis is on process mining and data mining
techniques and the combination of these methods for
process-oriented data. After a general introduction to the business
intelligence (BI) process and its constituent tasks in chapter 1,
chapter 2 discusses different approaches to modeling in BI
applications. Chapter 3 is an overview and provides details of data
provisioning, including a section on big data. Chapter 4 tackles
data description, visualization, and reporting. Chapter 5
introduces data mining techniques for cross-sectional data.
Different techniques for the analysis of temporal data are then
detailed in Chapter 6. Subsequently, chapter 7 explains techniques
for the analysis of process data, followed by the introduction of
analysis techniques for multiple BI perspectives in chapter 8. The
book closes with a summary and discussion in chapter 9. Throughout
the book, (mostly open source) tools are recommended, described and
applied; a more detailed survey on tools can be found in the
appendix, and a detailed code for the solutions together with
instructions on how to install the software used can be found on
the accompanying website. Also, all concepts presented are
illustrated and selected examples and exercises are provided. The
book is suitable for graduate students in computer science, and the
dedicated website with examples and solutions makes the book ideal
as a textbook for a first course in business intelligence in
computer science or business information systems. Additionally,
practitioners and industrial developers who are interested in the
concepts behind business intelligence will benefit from the clear
explanations and many examples.
The interaction of various ideas from different researchers
provides a main impetus to mathematical prosress. An important way
to make communication possible is through international conferences
on more or less spezialized topics~ The existence of several
centers for research in probabil ity and statistics in the eastern
part of central Europe - somewhat vaguely described as the
Pannonian area - led to the idea of organizing Pannonian Symposia
on Mathematical Statistics (PS~1S). The second such symposium was
held at Bad Tatzmannsdorf, Burgenland (Austria), from 14 to 20 June
1981. About 100 researchers from 13 countries participated in that
event and about 70 papers were delivered. Most of the papers dealt
with one of the following topics: nonparametric estimation theory,
asymptotic theory of estimation, invariance principles, limit
theorems and aoplications. Full versions of selected papers, all
presenting new results are included in this volume. The editors
take this opportunity to thank the following institutions for their
assistance in making the conference possible: the Provincial
Government of Burgenland, the Austrian Ministry for Research and
Science, the Burgenland Chamber of Commerce, the Control Data
Corporation, the Austrian Society for Statistics and Informatics,
the Landes- hypothekenbank Burgenland, the Volksbank Oberwart, and
the Community and Kurbad AG of Bad Tatzmannsdorf. We are also
greatly indebted to all those persons who helped in editing this
volume and in particular to the vii W. Grossmann et al. reds.),
Probability and Statistical Inference, vii-viii.
The Fourth Pannonian Symposium on Mathematical Statistics was held
in Bad Tatzmannsdorf, Austria, 4-10 September, 1983. The first two
Symposia were held there in 1979 and 1981; whereas the Third
Symposium was staged in Visegrad, Hungary in 1982. The proceedings
volumes of these conferences, published by Springer, D. Reidel, and
D. Reidel & Akademiai Kiad6, respec tively give information
about the objectives of the Pannonian Symposia and the topics
covered. About 130 participants from 17 countries took part in this
Fourth Symposium, and 92 lectures were presented. This volume
contains 21 reviewed contributions which cover various aspects of
the application of mathematical statistics. A second group of
papers dealing with problems of probability theory and decision
theory is published in a separate volume entitled "Probability and
Statistidal Decision Theory." Roughly speaking, the papers can be
grouped into three main categories. The first group is the
application of probability theory. A special type of application is
shown in the invited paper of P. Erdos, namely probabilistic
methods in number theory. Further models of applied probability
covered by the papers are game theory, urn models, best choice
models and random graphs. The second group could be best
characterized by the term mathematical statistics for models of
real data. Such models are linear models, regression,
discrimination, time series, analysis of censored data, goodness of
fit approxima tion of processes. The papers show the increasing
importance of VII new theoretical results (i. e."
This book assembles papers which were presented at the biennial
sympo sium in Computational Statistics held und er the a uspices of
the International Association for Statistical Computing (IASC), a
section of ISI, the Interna tional Statistical Institute. This
symposium named COMPSTAT '94 was organized by the Statistical
Institutes of the University of Vienna and the University of
Technology of Vienna, Austria. The series of COMPSTAT Symposia
started 1974 in Vienna. Mean while they took place every other year
in Berlin (Germany, 1976), Leiden (The Netherlands, 1978),
Edinburgh (Great Britain, 1980), Toulouse (France, 1982), Prague
(Czechoslovakia, 1984), Rom (Italy, 1986), Copenhagen (Den mark,
1988), Dubrovnik (Yugoslavia, 1990) and Neuchatel (Switzerland,
1992). This year we are celebrating the 20th anniversary in Vienna,
Austria. It has obviously been observed a movement from
"traditional" computa tional statistics with emphasis on methods
which produce results quickly and reliably, to computationally
intensive methods like resampling procedures, Bayesian methods,
dynamic graphics, to very recent areas like neural net works,
accentuation on spatial statistics, huge data sets, analysis
strategies, etc. For the organization of the symposium, new
guidelines worked out by the IASC in written form were in effect
this time. The goal was to refresh somehow the spirit of the start
of COMPSTAT '74, keep the tradition of the series and ensure a
certain continuity in the sequence of biannual meetings."
Proceedings of the 5th Pannonian Symposium, Visegrad, Hungary, May
20-24, 1985
The interaction of various ideas from different researchers
provides a main impetus to mathematical prosress. An important way
to make communication possible is through international conferences
on more or less spezialized topics~ The existence of several
centers for research in probabil ity and statistics in the eastern
part of central Europe - somewhat vaguely described as the
Pannonian area - led to the idea of organizing Pannonian Symposia
on Mathematical Statistics (PS~1S). The second such symposium was
held at Bad Tatzmannsdorf, Burgenland (Austria), from 14 to 20 June
1981. About 100 researchers from 13 countries participated in that
event and about 70 papers were delivered. Most of the papers dealt
with one of the following topics: nonparametric estimation theory,
asymptotic theory of estimation, invariance principles, limit
theorems and aoplications. Full versions of selected papers, all
presenting new results are included in this volume. The editors
take this opportunity to thank the following institutions for their
assistance in making the conference possible: the Provincial
Government of Burgenland, the Austrian Ministry for Research and
Science, the Burgenland Chamber of Commerce, the Control Data
Corporation, the Austrian Society for Statistics and Informatics,
the Landes- hypothekenbank Burgenland, the Volksbank Oberwart, and
the Community and Kurbad AG of Bad Tatzmannsdorf. We are also
greatly indebted to all those persons who helped in editing this
volume and in particular to the vii W. Grossmann et al. reds.),
Probability and Statistical Inference, vii-viii.
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