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Data Mining

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Book cover Frontiers of Expert Systems

Part of the book series: The Springer International Series in Engineering and Computer Science ((SECS,volume 552))

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Abstract

Data Mining, sometimes referred to as Knowledge Discovery in Databases (KDD), applies artificial intelligence, pattern recognition, and database techniques for the commercial analysis and exploitation of large amounts of data. No discussion of modern knowledge-based systems would be complete without mention of this important topic. Data Mining may be oriented towards discovering (a) summary descriptions and visualization of collections of data, (b) finding correlations among data attributes, (c) discriminating among classes using attribute values, (d) predicting values for output attributes, (e) identifying groups of similar data, or (f ) using historical information to predict the future values of variables. The following are some examples of data mining applications:

  • Fraud detection in the use of credit cards and accounts

  • Determination of the most appropriate target markets for a product

  • Association of market segments with specific marketing strategies

  • Analysis of medical histories to evaluate the risk of inheriting a disease

  • Determining consumption and usage patterns of customers

  • Projections of demand and supply of consumer products

  • Creditworthiness evaluation of loan applicants

  • Stock market predictions

Dirt-covered, a diamond lay hidden in the marketplace; fools passed, but only the wise would know its face, Kabirdas, c.1450

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Authors and Affiliations

  1. Syracuse University, USA

    Chilukuri Krishna Mohan

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  1. Chilukuri Krishna Mohan
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© 2000 Springer Science+Business Media New York

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Mohan, C.K. (2000). Data Mining. In: Frontiers of Expert Systems. The Springer International Series in Engineering and Computer Science, vol 552. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4509-5_9

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  • DOI: https://doi.org/10.1007/978-1-4615-4509-5_9

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7033-8

  • Online ISBN: 978-1-4615-4509-5

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