Gourt > Reference > Knowledge Management > Knowledge Discovery (13)
Data mining (DM), also known as Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining (KDD), is the process of automatically searching large volumes of data for patterns. Data mining is a fairly recent and contemporary topic in computer science. However, Data mining applies many older computational techniques from statistics, information retrieval, machine learning and pattern recognition.
Definition
Data mining can be defined as "the nontrivial extraction of implicit, previously unknown, and potentially useful information from data" W. Frawley and G. Piatetsky-Shapiro and C. Matheus, Knowledge Discovery in Databases: An Overview. AI Magazine, Fall 1992, pp. 213-228. and "the science of extracting useful information from large data sets or databases" D. Hand, H. Mannila, P. Smyth: Principles of Data Mining. MIT Press, Cambridge, MA, 2001. ISBN 0-262-08290-X. Although it is usually used in relation to analysis of data, data mining, like artificial intelligence, is an umbrella term and is used with varied meaning in a wide range of contexts. It is usually associated with a business or other organization's need to identify trends.
Data mining involves the process of analysing data to show patterns or relationships; sorting through large amounts of data; and picking out pieces of relative information or patterns that occur e.g., picking out statistical information from some data.
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KD Nuggets Tool Links - Tools for Data Mining and Knowledge Discovery. Comprehensive list of tools with Internet Links.
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Meta Description: [ Knowledge discovery in databases (KDD) is
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| and expert-based annotation delivers the optimal platform for knowledge discovery and understanding. ... text mining ... | |
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