Handbook of Massive Data Sets (Massive Computing)

by: James M Abello, Panos M Pardalos, Mauricio GC Resende

(31 March 2002)

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Abstract

The Handbook of Massive Data Sets is comprised of articles written by experts on selected topics that deal with some major aspect of massive data sets. It contains chapters on information retrieval both in the internet and in the traditional sense, web crawlers, massive graphs, string processing, data compression, clustering methods, wavelets, optimization, external memory algorithms and data structures, the US national cluster project, high performance computing, data warehouses, data cubes, semi-structured data, data squashing, data quality, billing in the large, fraud detection, and data processing in astrophysics, air pollution, biomolecular data, earth observation and the environment. The proliferation of massive data sets brings with it a series of special computational challenges. This "data avalanche" arises in a wide range of scientific and commercial applications.

@book{citeulike:2300852, abstract = {{The Handbook of Massive Data Sets is comprised of articles written by experts on selected topics that deal with some major aspect of massive data sets. It contains chapters on information retrieval both in the internet and in the traditional sense, web crawlers, massive graphs, string processing, data compression, clustering methods, wavelets, optimization, external memory algorithms and data structures, the US national cluster project, high performance computing, data warehouses, data cubes, semi-structured data, data squashing, data quality, billing in the large, fraud detection, and data processing in astrophysics, air pollution, biomolecular data, earth observation and the environment. The proliferation of massive data sets brings with it a series of special computational challenges. This "data avalanche" arises in a wide range of scientific and commercial applications. }}, author = {Abello, James M. and Pardalos, Panos M. and Resende, Mauricio G. C. }, citeulike-article-id = {2300852}, howpublished = {Hardcover}, isbn = {1402004893}, keywords = {algorithms}, month = {March}, posted-at = {2008-01-29 05:35:23}, priority = {2}, publisher = {Springer}, title = {Handbook of Massive Data Sets (Massive Computing)}, url = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20\&path=ASIN/1402004893}, year = {2002} }

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TY - BOOK ID - citeulike:2300852 L3 - citeulike-article-id:2300852 TI - Handbook of Massive Data Sets (Massive Computing) PB - Springer SN - 1402004893 N2 - {The Handbook of Massive Data Sets is comprised of articles written by experts on selected topics that deal with some major aspect of massive data sets. It contains chapters on information retrieval both in the internet and in the traditional sense, web crawlers, massive graphs, string processing, data compression, clustering methods, wavelets, optimization, external memory algorithms and data structures, the US national cluster project, high performance computing, data warehouses, data cubes, semi-structured data, data squashing, data quality, billing in the large, fraud detection, and data processing in astrophysics, air pollution, biomolecular data, earth observation and the environment. The proliferation of massive data sets brings with it a series of special computational challenges. This "data avalanche" arises in a wide range of scientific and commercial applications. } KW - algorithms AU - Abello, James AU - Pardalos, Panos AU - Resende, Mauricio PY - 2002/03/31/ UR - http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20&path=ASIN/1402004893 ER -

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