Introduction to Data Mining

You may also want to look at Data Mining Books

Data mining (also known as Knowledge Discovery in Databases - KDD) has been defined as "The nontrivial extraction of implicit, previously unknown, and potentially useful information from data"[1] It uses machine learning, statistical and visualization techniques to discover and present knowledge in a form which is easily comprehensible to humans.

Applications of Data Mining

Some example application areas are listed under Applications Of Data Mining

Net accessible resources

Two main websites provide information on data mining (including pointers to other relevant sites). They are

The Data Mine The Data Mining Wiki - The-Data-Mine.com

Featuring articles on data mining, a and information on Organizations Data Mining Organizations. It attempts to provide links to as much of the available data mining information on the net as is possible. Contributions to this effort are very welcome.

Knowledge Discovery Mine - kdnuggets.com

The Knowledge Discovery Mine has the KDD FAQ, a comprehensive catalog of tools for discovery in data, as well as back issues of the KDD-Nugget mailing list and surveys

Online Introductions

• Data Mining - An Introduction. Ruth Dilly, The Queen's University of Belfast -
• Kurt Thearling - "An Introduction to Data Mining" - thearling.com/text/dmwhite/dmwhite.htm
• Two Crows Introduction - "Introduction to Data Mining and Knowledge Discovery"

Journals

Business and Industry Publications

• DM Review - Covering Business Intelligence, Integration & Analytics - http://www.dmreview.com/
• Intelligent Enterprise - Business Intelligence focus - http://www.intelligententerprise.com/

Academic Journals

• Applied Intelligence - The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies
• Data Mining and Knowledge Discovery
• Journal of Intelligent Information Systems - Integrating Artificial Intelligence and Database Technologies
• Journal of Intelligent Systems
• Knowledge and Information Systems
• Machine Learning
• IEEE Transactions on Knowledge and Data Engineering
• IEEE Transactions on Pattern Analysis and Machine Intelligence
• Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery publishes review articles. Launched January 2011

Introductory Articles

[1] W. Frawley and G. Piatetsky-Shapiro and C. Matheus, Knowledge Discovery in Databases: An Overview. AI Magazine, Fall 1992, pgs 213-228

[2] "State of The Art" in Byte Magazine October 1995, contains three articles on Data Mining and Data Warehousing

[3] W. H. Inmon and S. Osterfelt, Understanding Data Pattern Processing QED Techincal Publishing Group, 1991, Wellesley, MA. I haven't see this book myself, but I saw describe it as "a business-oriented, nontechnical book"

[4] Cheryl Gerber, Excavate Your Data. Datamation 42(9), May 1996. "Datamining could be your No. 1 strategic weapon--and source of profit--in dissecting archival information. But with its roots in machine learning, this esoteric technology takes some time to master."

[5] Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth, and Ramasamy Uthurusamy, Advances in Knowledge Discovery and Data Mining. Published by the AAAI Press / The MIT Press

[6] Herb Edelstein, Data Mining: Exploiting the Hidden Trends in Your Data. DB2 Online Magazine.

"This article, adapted from the Two Crows report "Data Mining: Products, Applications, Technology," introduces you to data mining technology and explains how IBM's Intelligent Miner can help you exploit hidden trends in your data."

With recent tremendous technical advances in processing power, storage capacity, and inter-connectivity of computer technology, data mining is seen as an increasingly important tool by modern business to transform unprecedented quantities of digital data into business intelligence giving an in a wide range of profiling practices, such as marketing, surveillance, fraud detection, and scientific discovery. The growing consensus that data mining can bring real value has led to an explosion in demand for novel data mining technologies.

Larger Bibliography

See: Data Mining Bibliographies

See also:

• Introduction To Data Mining Association Rules
• Introduction To OLAP
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