With the objective of learning data mining concepts and also applying them to my MS course project(I had promised to talk about this in one of my earlier posts), I happened to explore and compile links to some books, blogs, articles, papers etc. Here’s listing of those and it is useful to anyone who’s interested in Data Mining, Text Mining, NLP, Information Retrieval and related areas. This can serve up as a one-stop location, for my quick reference as well! 🙂
Academic/University Stuff:
http://infolab.stanford.edu/~ullman/mining/2009/index.html
http://www.cs.waikato.ac.nz/ml/weka/
http://www.cs.waikato.ac.nz/~ihw/papers/04-IHW-Textmining.pdf
http://www.laits.utexas.edu/~norman/BUS.FOR/course.mat/Alex/#9
http://www.cs.umbc.edu/~nicholas/clustering/
http://web.ccsu.edu/datamining/resources.html
http://www.stanford.edu/class/cs276/
http://www.cs.sunysb.edu/~cse634/presentations/TextMining.pdf
http://scpd.stanford.edu/ppc/kdnuggets-2011-04.jsp?_vsrefdom=EmailMarketing
http://ocw.mit.edu/courses/sloan-school-of-management/15-062-data-mining-spring-2003/lecture-notes/
http://www.crisp-dm.org/Process/index.htm
http://www.the-data-mine.com/
http://www.kdnuggets.com/
http://www.csc.kth.se/~rosell/undervisning/sprakt/irintro060801.pdf http://www.autonlab.org/tutorials/kmeans.html
http://filebox.vt.edu/users/wfan/text_mining.html
http://people.ischool.berkeley.edu/~hearst/research.html
Books:
Introduction to Data Mining by Pang-Ning Tan, Michael Steinbach, Vipin Kumar
Collective Intelligence in Action by Satnam Alag
Introduction to Modern Information Retrieval (Popular book)by G. Salton, Gerard
Companies:
http://www.oracle.com/technetwork/database/options/odm/index.html
http://download.oracle.com/docs/html/B14340_01/java_using.htm
http://www.dataminingcasestudies.com/
http://www.kxen.com/Products/Explorer/Text+Analytics
http://www.sas.com/textminer
http://www.ibm.com/developerworks/library/wa-wbdm/
http://www.developertutorials.com/tutorials/java/java-data-mining-822/
http://www2.parc.com/istl/projects/ia/sg-clustering.html
ACM KDD Special Interest Group
Papers:
Ontology-based Distance Measure for Text Clustering
Data Mining: Extending the Information Warehouse Framework
Pragmatic Text Mining: Minimizing Human Effort to Quantify Many
Issues in Call Logs
Better Rules, Fewer Features: A Semantic Approach to Selecting Features from Text
Blogs:
http://irthoughts.wordpress.com/about/
http://glinden.blogspot.com/2006/11/excellent-data-mining-lecture-notes.html
http://sujitpal.blogspot.com/2009_09_01_archive.html
http://www.kdnuggets.com/websites/blogs.html
Analytics:
http://www.kaushik.net/avinash/
NLP:
http://nlpers.blogspot.com/search/label/sentiment
http://blog.sematext.com/
Mother Link for Data Mining Resources from a Librarian(mayn’t find all those mentioned above though!)