Data Mining Applications for Empowering Knowledge SocietiesHakikur Rahman Information Science Reference, 2009 - 332 pàgines Data Mining techniques are gradually becoming essential components of corporate intelligence systems and progressively evolving into a pervasive technology within activities that range from the utilization of historical data to predicting the success of an awareness campaign. In reality, data mining is becoming an interdisciplinary field driven by various multi-dimensional applications. Data Mining Applications for Empowering Knowledge Societies presents an overview on the main issues of data mining, including its classification, regression, clustering, and ethical issues. This comprehensive book also provides readers with knowledge enhancing processes as well as a wide spectrum of data mining applications. |
Continguts
Chapter II | 26 |
Chapter III | 43 |
Detecting Deforestation Patterns Through Satellites | 55 |
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Data Mining Applications for Empowering Knowledge Societies Rahman, Hakikur Previsualització limitada - 2008 |
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2-itemsets Accuracy analysis approach areas association rules candidate portfolios challenges chapter Chen clustering companies concept credit card customers data mining data mining algorithms data mining applications data mining techniques data warehouse database decision tree deforestation detection developing countries directed graph drought dynamic hash ensemble extract hash table identified IEEE IGI Global image mining implementation improve integrated intelligence International Conference Internet Journal knowledge discovery linear programming machine learning marketing MCLP MCQP methods monitoring multiple criteria nanotechnology neural networks neuronal one-sum weighted prediction problems Proceedings quadratic programming relationship remote sensing remote sensing image Retrieved April 13 RFID risk SMEs social spatial patterns strategies Table testing dataset threshold tion transactions variables Wal-Mart Wang Web mining Web usage mining weighted itemset