Data Mining for Social Network Data, Memon

Автор: С.Aggarwal
Название: Data Mining: The Textbook
ISBN: 3319141414 ISBN-13(EAN): 9783319141411
Издательство: Springer
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Цена: 9781.00 р.
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Описание: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.

Автор: Lars Eld?n
Название: Matrix Methods in Data Mining and Pattern Recognition
ISBN: 0898716268 ISBN-13(EAN): 9780898716269
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.

Автор: Clara Pizzuti; Marylyn D. Ritchie; Mario Giacobini
Название: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
ISBN: 3642011837 ISBN-13(EAN): 9783642011832
Издательство: Springer
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Цена: 9781.00 р.
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Описание: Constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2009, held in Tubingen, Germany, in April 2009 co located with the Evo 2009 events. This book includes such topics as biomarker discovery, cell simulation and modeling, and ecological modeling.

Название: Data Mining & Business
ISBN: 1930708033 ISBN-13(EAN): 9781930708037
Издательство: Mare Nostrum (Eurospan)
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Цена: 11872.00 р.
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Описание: An overview of data mining technology and how it is applied in a business environment. Methodologies are described that solve a variety of business problems and enhance firm-level efficiency in a less technical, managerial style. The book also incorporates the data mining process into the spectrum of complementary technologies that together comprise corporate information systems that promote "business intelligence". Business intelligence involves the proliferation of value-added information throughout a given enterprise through the use of various software applications that promote efficiency for the firm.

Автор: Sameer Singh; Maneesha Singh; Chid Apte; Petra Per
Название: Pattern Recognition and Data Mining
ISBN: 3540287574 ISBN-13(EAN): 9783540287575
Издательство: Springer
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Цена: 16769.00 р.
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Описание: Constitutes the refereed proceedings of the Third International Conference on Advances in Pattern Recognition, ICAPR 2005, held in Bath, UK in August 2005.

Автор: Finlay Steven
Название: Predictive Analytics, Data Mining and Big Data
ISBN: 1137379278 ISBN-13(EAN): 9781137379276
Издательство: Springer
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Цена: 5589.00 р.
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Описание: This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319419196 ISBN-13(EAN): 9783319419190
Издательство: Springer
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Цена: 13416.00 р.
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Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.