Posts tagged: book

Reactive Business Intelligence

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By Volkan TUNALI, December 25, 2010 3:14 pm

Reactive Business Intelligence - coverI’ve recently found an interesting data analysis and visualization book: Reactive Business Intelligence: From Data to Models to Insight by Roberto Battiti and Mauro Brunato.

The book explains data analysis concepts in an easy and intuitive way, supported with visual elements. It is freely available for download at http://grapheur.com/static/Battiti-Brunato-RBI.pdf.








There are also funny pictures that depict the subject. Below are two examples of such pictures I find very nice. I hope the authors don’t mind me putting them here. :)


Figure 7.1 from page 42 – Clustering.


Figure 17.1 from page 167 – Local search.
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Update April 6, 2011: A little note from the authors:
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Dear colleague:

Our latest book is now printed:

Reactive Business Intelligence. From Data to Models to Insight.
R. Battiti and M. Brunato,
Reactive Search Srl, Italy, February 2011.
ISBN: 978-88-905795-0-9

Full details at the book web site:

http://www.reactivebusinessintelligence.com/

Reactive Business Intelligence is about integrating data mining,
modeling and interactive visualization, into an end-to-end
discovery and continuous innovation process powered
by human and automated learning.
This holistic and unifying goal requires collecting and integrating
topics which are usually dissected in books dedicated to
different areas.

We plan to place figures and slides in the same place very soon.

– Roberto Battiti and Mauro Brunato
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Guide to Intelligent Data Analysis

By Volkan TUNALI, December 22, 2010 11:03 pm

I want to introduce a new Data Mining book from Springer: Guide to Intelligent Data Analysis. This book provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems.

Authors: Michael R. Berthold (University of Konstanz, Germany), Christian Borgelt (European Centre for Soft Computing, Spain), Frank Höppner (Ostfalia University of Applied Sciences, Germany), Frank Klawonn (Ostfalia University of Applied Sciences, Germany).
Publisher: Springer
ISBN: 978-1-84882-259-7

In the book, chapters proceed with examples where KNIME and/or R are used as analysis tools. In addition, two chapters of appendices are dedicated to KNIME and R.

This is an excellent book which contains a very good combination of both theory and practice of data analysis. I strongly recommend this book to data mining researchers. For more information you can visit Springer page of the book.

Fundamentals of Predictive Text Mining

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By Volkan TUNALI, September 4, 2010 11:09 pm

Fundamentals of Predictive Text MiningFundamentals of Predictive Text Mining is the new book I’ve found recently about text mining. This book explains the essentials of text mining very very well with very good examples, so I strongly recommend it to the newcomers to the field. Although the goal of the book is predictive text mining, its content is sufficiently broad to cover such topics as text clustering, information retrieval, and information extraction.

The book also contains several case studies that find solutions to several real life problems.

Authors: Sholom M. Weiss, Nitin Indurkyha, Tong Zhang
ISBN: 9781849962254
Publisher: Springer

Introduction to Information Retrieval

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By Volkan TUNALI, September 1, 2010 11:36 pm

Introduction to Information RetrievalI will introduce a new book I find very useful: Introduction to Information Retrieval by Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, from Cambridge University Press (ISBN: 0521865719).

The book provides a modern approach to information retrieval from a computer science perspective. It is based on a course the authors have been teaching in various forms at Stanford University and at the University of Stuttgart.

It contains the following chapters:

  1. Boolean retrieval
  2. The term vocabulary & postings lists
  3. Dictionaries and tolerant retrieval
  4. Index construction
  5. Index compression
  6. Scoring, term weighting & the vector space model
  7. Computing scores in a complete search system
  8. Evaluation in information retrieval
  9. Relevance feedback & query expansion
  10. XML retrieval
  11. Probabilistic information retrieval
  12. Language models for information retrieval
  13. Text classification & Naive Bayes
  14. Vector space classification
  15. Support vector machines & machine learning on documents
  16. Flat clustering
  17. Hierarchical clustering
  18. Matrix decompositions & latent semantic indexing
  19. Web search basics
  20. Web crawling and indexes
  21. Link analysis

The book is freely available for download in PDF format at http://nlp.stanford.edu/IR-book/information-retrieval-book.html (as a whole or as individual chapters).

Data Mining Books

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By Volkan TUNALI, June 23, 2010 8:25 pm

The following are the books I think very useful for beginners as well as advanced researchers in data mining field.

Data Mining: Concepts and Techniques, Second Edition

Data Mining: Concepts and Techniques, Second Edition

Authors: Jiawei HanMicheline Kamber
Publisher: Morgan Kaufmann Publishers

This may be the most known data mining book. I recommend especially to beginners.








Introduction to Data Mining

Introduction to Data Mining

Authors: Pang-Ning TanMichael SteinbachVipin Kumar
Publisher: Addisson-Wesley










Grouping Multidimensional Data: Recent Advances in Clustering

Grouping Multidimensional Data: Recent Advances in Clustering

Authors: Jacob Kogan, Charles Nicholas, Marc Teboulle (Editors)
Publisher: Springer














There are other books I really like. I’ll introduce them later.

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