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Data Mining Mengolah Data Menjadi Informasi menggunakan Matlab

Scientific Data Mining

A Practical Perspective

Chandrika Kamath describes how techniques from the multi-disciplinary field of data mining can be used to address the modern problem of data overload in science and engineering domains. Starting with a survey of analysis problems in different applications, it identifies the common themes across these domains.

Chandrika Kamath describes how techniques from the multi-disciplinary field of data mining can be used to address the modern problem of data overload in science and engineering domains.

Compilation of Correspondence and Statistical Data from the Records and Files of the Department of the Interior in Relation to Coal Lands in the Indian Territory

The Acreage and Approximate Value Thereof, the Thickness of the Various Veins of Coal, Etc. March 27, 1906, to June 30, 1906

12,647 10,128 4,360 - 14,488 18 Folsom,Morris Coal Mining Co., The .......... . .
34,362 4. 727 3,122 7.849 $3 }Gr8l1l Western C00.l and Coke C0., The ........ ..
196. 978 97,579 106.668 . 204,247 21 I1aile.v,W. E ...

Data Mining

Federal Efforts Cover a Wide Range of Uses : Report to the Ranking Minority Member, Subcomittee on Financial Management, the Budget, and International Security, Committee on Governmental Affairs, U.S. Senate

Data mining is becoming a big business; Forrester Research has estimated that
the data mining market is passing the billion dollar mark. Although the use and
sophistication of data mining have increased in both the government and the ...

Data Mining V

Yielding substantial knowledge from data primarily gathered for a wide range of quite different applications, data mining is a promising and relatively new area of current research and development. This book features papers from the Fifth International Conference on Data Mining. Text Mining and Their Business Applications. Sharing state-of-the-art results and practical development experiences, these allow researchers and applications developers from a variety of areas to learn about the many different applications of data mining and how the techniques can help in their own field. The volume features contributions on topics such as: Data Preparation - Data Selection; Preprocessing; Transformation. Techniques - Neural Networks; Decision Trees; Genetic Algorithms; Information Extraction; Clustering; Categorization. Special Applications - Customer Relationship Management; Competitive Intelligence.

Besides, from Web Mining, new research areas were derived to guide the
solutions to its specific needs. In short, some researchers have worked on mining
the content of a web site (web content mining), others have decided to study the ...

Data Warehousing and Mining

Concepts, Methodologies, Tools, and Applications

"This collection offers tools, designs, and outcomes of the utilization of data mining and warehousing technologies, such as algorithms, concept lattices, multidimensional data, and online analytical processing. With more than 300 chapters contributed by over 575 experts from around the globe, this authoritative collection will provide libraries with the essential reference on data mining and warehousing"--Provided by publisher.

"This collection offers tools, designs, and outcomes of the utilization of data mining and warehousing technologies, such as algorithms, concept lattices, multidimensional data, and online analytical processing.