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I'm working on a small (200M) corpus of text, which I want to explore with some cluster analysis. What books or articles on that subject would you recommend?

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8 Answers 8

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It may be worth looking at M.W. Berry's books:

  1. Survey of Text Mining I: Clustering, Classification, and Retrieval (2003)
  2. Survey of Text Mining II: Clustering, Classification, and Retrieval (2008)

They consist of series of applied and review papers. The latest seems to be available as PDF at the following address: http://bit.ly/deNeiy.

Here are few links related to CA as applied to text mining:

You can also look at Latent Semantic Analysis, but see my response there: Working through a clustering problem.

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Finding Groups in Data. An Introduction to Cluster Analysis from professors Leonard Kaufman and Peter J. Rousseeuw.

I am reading the book and finding it very useful because:

  • As stated by the authors in the preface:

Our purpose was to write an applied book for the general user. We wanted to make cluster analysis available to people who do not necessarily have a strong mathematical or statistical background.

  • It provides theoretical content to understand the functions available in the R package Cluster.

  • Chapters can be read individually according to the cluster method of interest.
    exception is chapter 3, which is built on chapter 2

The book's chapters are:

  1. Introduction
  2. Partitioning Around Medoids (Program PAM).
  3. Clustering Large Applications (Program CLARA).
  4. Fuzzy Analysis (Program FUNNY).
  5. Agglomerative Nesting (Program AGNES).
  6. Divisive Analysis (Program DIANA).
  7. Monothetic Analysis (Program MONA).

References:

Kaufman, L., & Rousseeuw, P. J. (2005). Finding Groups in Data. An Introduction to Cluster Analysis (p. 342). John Wiley & Sons Inc.

Maechler, M. (2013). Cluster Analysis Extended Rousseeuw et al. CRAN.

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    $\begingroup$ This book indeed provides a nice overview of the field. It focuses on a few algorithms/methods (e.g. the well-known silhouette, which happens to have been designed by one of the book's authors) and covers them extensively. It also comes with some code, but 1990 style. FYI: full table of contents. $\endgroup$
    – Franck Dernoncourt
    Nov 26, 2013 at 14:03
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This chapter of Introduction to Data Mining is available online and gives a nice overview.

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  • $\begingroup$ And here is the link to the 2nd edition (2018). $\endgroup$
    – Richard Hardy
    Jan 10, 2019 at 10:28
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Cluster Analysis by Brian S. Everitt is a nice book length applied treatment of Cluster Analysis.

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Another in-depth book worth looking at: Handbook of Cluster Analysis by Hennig et al. (2015)

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Not specifically about text-mining, but I quite liked "Exploratory Data Analysis with MATLAB" by Martinez and Martinez.

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From an statistical viewpoint there is Model-Based Clustering and Classification for Data Science which uses R for the examples. The book is by Charles Bouveyron et al (2019)

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I am not sure what software you use, but this book is a good one if you are using R. It covers many common unsupervised learning algorithms with good examples!

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