Institution
Mitre Corporation
Company•Bedford, Massachusetts, United States•
About: Mitre Corporation is a company organization based out in Bedford, Massachusetts, United States. It is known for research contribution in the topics: Air traffic control & National Airspace System. The organization has 4884 authors who have published 6053 publications receiving 124808 citations. The organization is also known as: Mitre & MITRE.
Papers published on a yearly basis
Papers
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01 Jun 1998TL;DR: The general idea, called “query flocks,” is a generate-and-test model for data-mining problems and is shown how the idea can be used either in a general-purpose mining system or in a next generation of conventional query optimizers.
Abstract: Association-rule mining has proved a highly successful technique for extracting useful information from very large databases. This success is attributed not only to the appropriateness of the objectives, but to the fact that a number of new query-optimization ideas, such as the “a-priori” trick, make association-rule mining run much faster than might be expected. In this paper we see that the same tricks can be extended to a much more general context, allowing efficient mining of very large databases for many different kinds of patterns. The general idea, called “query flocks,” is a generate-and-test model for data-mining problems. We show how the idea can be used either in a general-purpose mining system or in a next generation of conventional query optimizers.
194 citations
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TL;DR: Synthea, an open-source software package that simulates the lifespans of synthetic patients, modeling the 10 most frequent reasons for primary care encounters and the 10 chronic conditions with the highest morbidity in the United States is developed.
191 citations
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TL;DR: Why incorporating an understanding of human behavior into cyber security products and processes can lead to more effective technology is described and how behavioral science offers the potential for significant increases in the effectiveness of cyber security is illustrated.
190 citations
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Marine Biological Laboratory1, European Bioinformatics Institute2, Michigan State University3, Ghent University4, University of Chicago5, Argonne National Laboratory6, Max Planck Society7, Mitre Corporation8, National Institutes of Health9, DSM10, University of Colorado Boulder11, Joint Genome Institute12, University of New Mexico13, University of Oxford14, University of Maryland, Baltimore15, Wellcome Trust Sanger Institute16, Technical University of Denmark17, University of California, San Diego18
TL;DR: A short history of the GSC is provided, an overview of its range of current activities are provided, and a call for the scientific community to join forces to improve the quality and quantity of contextual information about the authors' public collections of genomes, metagenomes, and marker gene sequences is made.
Abstract: A vast and rich body of information has grown up as a result of the world's enthusiasm for 'omics technologies. Finding ways to describe and make available this information that maximise its usefulness has become a major effort across the 'omics world. At the heart of this effort is the Genomic Standards Consortium (GSC), an open-membership organization that drives community-based standardization activities, Here we provide a short history of the GSC, provide an overview of its range of current activities, and make a call for the scientific community to join forces to improve the quality and quantity of contextual information about our public collections of genomes, metagenomes, and marker gene sequences.
190 citations
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TL;DR: In this paper, the problem of finding the simulated system with the best (maximum or minimum) expected performance when the number of systems is large and initial samples from each system have already been taken is addressed.
Abstract: In this paper we address the problem of finding the simulated system with the best (maximum or minimum) expected performance when the number of systems is large and initial samples from each system have already been taken This problem may be encountered when a heuristic search procedure--perhaps one originally designed for use in a deterministic environment--has been applied in a simulation-optimization context Because of stochastic variation, the system with the best sample mean at the end of the search procedure may not coincide with the true best system encountered during the search This paper develops statistical procedures that return the best system encountered by the search (or one near the best) with a prespecified probability We approach this problem using combinations of statistical subset selection and indifference-zone ranking procedures The subset-selection procedures, which use only the data already collected, screen out the obviously inferior systems, while the indifference-zone procedures, which require additional simulation effort, distinguish the best from the less obviously inferior systems
190 citations
Authors
Showing all 4896 results
Name | H-index | Papers | Citations |
---|---|---|---|
Sushil Jajodia | 101 | 664 | 35556 |
Myles R. Allen | 82 | 295 | 32668 |
Barbara Liskov | 76 | 204 | 25026 |
Alfred D. Steinberg | 74 | 295 | 20974 |
Peter T. Cummings | 69 | 521 | 18942 |
Vincent H. Crespi | 63 | 287 | 20347 |
Michael J. Pazzani | 62 | 183 | 28036 |
David Goldhaber-Gordon | 58 | 192 | 15709 |
Yeshaiahu Fainman | 57 | 648 | 14661 |
Jonathan Anderson | 57 | 195 | 10349 |
Limsoon Wong | 55 | 367 | 13524 |
Chris Clifton | 54 | 160 | 11501 |
Paul Ward | 52 | 408 | 12400 |
Richard M. Fujimoto | 52 | 290 | 13584 |
Bhavani Thuraisingham | 52 | 563 | 10562 |