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Titlebook: Mining Very Large Databases with Parallel Processing; Alex A. Freitas,Simon H. Lavington Book 2000 Springer Science+Business Media New Yor

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發(fā)表于 2025-3-21 16:08:51 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Mining Very Large Databases with Parallel Processing
編輯Alex A. Freitas,Simon H. Lavington
視頻videohttp://file.papertrans.cn/635/634674/634674.mp4
叢書名稱Advances in Database Systems
圖書封面Titlebook: Mining Very Large Databases with Parallel Processing;  Alex A. Freitas,Simon H. Lavington Book 2000 Springer Science+Business Media New Yor
描述.Mining Very Large Databases with Parallel Processing.addresses the problem of large-scale data mining. It is aninterdisciplinary text, describing advances in the integration ofthree computer science areas, namely `intelligent‘ (machinelearning-based) data mining techniques, relational databases andparallel processing. The basic idea is to use concepts and techniquesof the latter two areas - particularly parallel processing- to speed up and scale up data mining algorithms. .The book is divided into three parts. The first part presents acomprehensive review of intelligent data mining techniques such asrule induction, instance-based learning, neural networks and geneticalgorithms. Likewise, the second part presents a comprehensive reviewof parallel processing and parallel databases. Each of these partsincludes an overview of commercially-available, state-of-the-arttools. The third part deals with the application of parallelprocessing to data mining. The emphasis is on finding generic,cost-effective solutions for realistic data volumes. Two parallelcomputational environments are discussed, the first excluding the useof commercial-strength DBMS, and the second using parallel DBMSserver
出版日期Book 2000
關(guān)鍵詞DBMS; algorithms; artificial intelligence; computer science; data mining; database; database systems; genet
版次1
doihttps://doi.org/10.1007/978-1-4615-5521-6
isbn_softcover978-1-4613-7523-4
isbn_ebook978-1-4615-5521-6Series ISSN 1386-2944
issn_series 1386-2944
copyrightSpringer Science+Business Media New York 2000
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Advances in Database Systemshttp://image.papertrans.cn/m/image/634674.jpg
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https://doi.org/10.1007/978-1-4615-5521-6DBMS; algorithms; artificial intelligence; computer science; data mining; database; database systems; genet
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Book 2000ls with the application of parallelprocessing to data mining. The emphasis is on finding generic,cost-effective solutions for realistic data volumes. Two parallelcomputational environments are discussed, the first excluding the useof commercial-strength DBMS, and the second using parallel DBMSserver
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Mining Very Large Databases with Parallel Processing
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From Search Engines to Question-Answering Systems — The Need for New Toolssynthesize an answer to a query by drawing on bodies of information which are resident in various parts of the knowledge base. It is this capability that differentiates a question-answering system, Q/A system for short, from a search engine.
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