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Books > Computing & IT > General theory of computing
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Computer and Information Science (Hardcover, 2008 ed.)
Loot Price: R2,810
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Computer and Information Science (Hardcover, 2008 ed.)
Series: Studies in Computational Intelligence, 131
Expected to ship within 18 - 22 working days
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Thepurposeofthe
7thIEEE/ACISInternationalConferenceonComputerandInfor- tion Science
(ICIS2008)and the 2nd IEEE/ACISInternationalWorkshop on e-Activity
(IWEA 2008) to be held on May 14-16, 2008 in Portland, Oregon,
U.S.A. is to bring together scientists, engineers, computer users,
and students to share their experiences and exchange new ideas and
research results about all aspects (theory, applications and tools)
of computer and information science; and to discuss the practical
challenges - countered along the way and the solutions adopted to
solve them. In January, 2008 one of editors of this book approached
in house editor Dr. Thomas
Ditzingeraboutpreparingavolumecontainingextendedandimprovedversionsofsome
of the papers selected for presentation at the conference and
workshop. Upon receiving Dr. Ditzinger's approval, conference
organizers selected 23 outstanding papers from ICIS/IWEA 2008, all
of which you will nd in this volume of Springer's Studies in
Computational Intelligence. In chapter 1, Fabio Perez Marzullo et
al. describe a model driven architecture (MDA) approachfor
assessing database performance.The authorspresent a pro ling
technique that offers a way to assess performance and identify aws,
while performing software construction activities. In chapter 2,
authorsHuy Nguyen Anh Pham and EvangelosTriantaphyllouoffera new
approachfortesting classi cation algorithms, and present
thisapproachthroughrean- ysis of the Pima Indian diabetes dataset,
one of the most well-known datasets used for this purpose. The new
method put forth by the authors is dubbed the Homogeneity- Based
Algorithm(HBA), and it aims to optimally control the over ttingand
overgen- alization behaviors that have proved problematic for
previous classi cation algorithms on this dataset.
General
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