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Glossaries for computing and data processing
Communications of the ACM, 1961At the present time, there is considerable interest and activity in the preparation of a comprehensive glossary of computing and data processing terms. This interest is generated by members of the various national and international professional associations, the computer manufacturers, and the American Standards Association.
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Applications in Data-Intensive Computing
2010Abstract The total quantity of digital information in the world is growing at an alarming rate. Scientists and engineers are contributing heavily to this data “tsunami” by gathering data using computing and instrumentation at incredible rates. As data volumes and complexity grow, it is increasingly arduous to extract valuable information from the ...
Anuj R. Shah +21 more
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Data intensive computing---Data intensive computing
Proceedings of the 2006 ACM/IEEE conference on Supercomputing - SC '06, 2006Leslie S Perkins +6 more
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Privacy and computer data banks
ACM SIGCAS Computers and Society, 1978The right to privacy is becoming one of the key issues of our times. The single biggest threat to individual privacy is the "computer data bank". It has only been since the mid-sixties that personal privacy and the computer data bank have collided.
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2014
The applied data-centric social sciences are cyber-enabled and require the use of inductive strategies to define problems and challenges. Thus, we require the use of computers to process a large number of data points. In this chapter, we will see how computers can be used to acquire, handle and analyse data.
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The applied data-centric social sciences are cyber-enabled and require the use of inductive strategies to define problems and challenges. Thus, we require the use of computers to process a large number of data points. In this chapter, we will see how computers can be used to acquire, handle and analyse data.
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Computational Aspects of Data Mining
2003The last decade has witnessed an impressive growth of Data Mining through algorithms and applications. Despite the advances, a computational theory of Data Mining is still largely outstanding. This paper discusses some aspects relevant to computation in Data Mining from the point of view of the Machine Learning theoretician.
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