Recommended books or articles as introduction to Cluster Analysis? 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?  
 A: It may be worth looking at M.W. Berry's books: 


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*Survey of Text Mining I: Clustering, Classification, and Retrieval (2003)

*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: 


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*Document Topic Generation in Text Mining by Using Cluster Analysis with EROCK

*An Approach to Text Mining using Information Extraction
You can also look at Latent Semantic Analysis, but see my response there: Working through a clustering problem. 
A: 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:


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*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.



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*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:


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*Introduction

*Partitioning Around Medoids (Program PAM).

*Clustering Large Applications (Program CLARA).

*Fuzzy Analysis (Program FUNNY).  

*Agglomerative Nesting (Program AGNES).  

*Divisive Analysis (Program DIANA).   

*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.
A: This chapter of Introduction to Data Mining is available online and gives a nice overview. 
A: Cluster Analysis by Brian S. Everitt is a nice book length applied treatment of Cluster Analysis.
A: Another in-depth book worth looking at:
Handbook of Cluster Analysis by Hennig et al. (2015)
A: Not specifically about text-mining, but I quite liked "Exploratory Data Analysis with MATLAB" by Martinez and Martinez.
A: 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)
A: 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!
