Scalable High Performance Computing For Knowledge Discovery And Data Mining


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Scalable High Performance Computing for Knowledge Discovery and Data Mining


Scalable High Performance Computing for Knowledge Discovery and Data Mining

Author: Paul Stolorz

language: en

Publisher: Springer Science & Business Media

Release Date: 2012-12-06


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Scalable High Performance Computing for Knowledge Discovery and Data Mining brings together in one place important contributions and up-to-date research results in this fast moving area. Scalable High Performance Computing for Knowledge Discovery and Data Mining serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

Scalable High Performance Computing for Knowledge Discovery and Data Mining


Scalable High Performance Computing for Knowledge Discovery and Data Mining

Author: Paul Stolorz

language: en

Publisher: Springer Science & Business Media

Release Date: 1998-01-31


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Scalable High Performance Computing for Knowledge Discovery and Data Mining brings together in one place important contributions and up-to-date research results in this fast moving area. Scalable High Performance Computing for Knowledge Discovery and Data Mining serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

Large-Scale Parallel Data Mining


Large-Scale Parallel Data Mining

Author: Mohammed J. Zaki

language: en

Publisher: Springer

Release Date: 2003-07-31


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With the unprecedented growth-rate at which data is being collected and stored electronically today in almost all fields of human endeavor, the efficient extraction of useful information from the data available is becoming an increasing scientific challenge and a massive economic need. This book presents thoroughly reviewed and revised full versions of papers presented at a workshop on the topic held during KDD'99 in San Diego, California, USA in August 1999 complemented by several invited chapters and a detailed introductory survey in order to provide complete coverage of the relevant issues. The contributions presented cover all major tasks in data mining including parallel and distributed mining frameworks, associations, sequences, clustering, and classification. All in all, the volume presents the state of the art in the young and dynamic field of parallel and distributed data mining methods. It will be a valuable source of reference for researchers and professionals.