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Distributed distance matrix generator based on agents

Published: 13 June 2012 Publication History

Abstract

The process of calculating similarities between different time series of a dataset -- i.e. a distance matrix -- is often very time-consuming, but can be sped-up significantly using distributed programming. This paper presents a distributed system for calculating the distance matrix that utilizes the agent technology. Software agents are employed to deal with dynamic properties of the computational network, such as sudden unavailability of a number of computers, as well as for load-balancing and task-sharing.

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Cited By

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  • (2022)Elastic distances for time-series classification: Itakura versus Sakoe-Chiba constraintsKnowledge and Information Systems10.1007/s10115-022-01725-164:10(2797-2832)Online publication date: 12-Aug-2022
  • (2020)A Study of the State of the Art in Synthetic Emotional Intelligence in Affective ComputingNatural Language Processing10.4018/978-1-7998-0951-7.ch058(1199-1212)Online publication date: 2020
  • (2016)A Study of the State of the Art in Synthetic Emotional Intelligence in Affective ComputingInternational Journal of Synthetic Emotions10.4018/IJSE.20160101017:1(1-12)Online publication date: 1-Jan-2016
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Published In

cover image ACM Other conferences
WIMS '12: Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
June 2012
571 pages
ISBN:9781450309158
DOI:10.1145/2254129
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • UCV: University of Craiova
  • WNRI: Western Norway Research Institute

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 June 2012

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Author Tags

  1. distributed programming
  2. software agents
  3. time-series analysis

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  • Research-article

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WIMS '12
Sponsor:
  • UCV
  • WNRI

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Overall Acceptance Rate 140 of 278 submissions, 50%

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Cited By

View all
  • (2022)Elastic distances for time-series classification: Itakura versus Sakoe-Chiba constraintsKnowledge and Information Systems10.1007/s10115-022-01725-164:10(2797-2832)Online publication date: 12-Aug-2022
  • (2020)A Study of the State of the Art in Synthetic Emotional Intelligence in Affective ComputingNatural Language Processing10.4018/978-1-7998-0951-7.ch058(1199-1212)Online publication date: 2020
  • (2016)A Study of the State of the Art in Synthetic Emotional Intelligence in Affective ComputingInternational Journal of Synthetic Emotions10.4018/IJSE.20160101017:1(1-12)Online publication date: 1-Jan-2016
  • (2016)Comparison of different weighting schemes for the kNN classifier on time-series dataKnowledge and Information Systems10.1007/s10115-015-0881-048:2(331-378)Online publication date: 1-Aug-2016
  • (2014)Emotional Intelligence and AgentsProceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14)10.1145/2611040.2611100(1-7)Online publication date: 2-Jun-2014

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