Multi-agents based data mining for intelligent decision support systems

Dharmendra SHARMA, Fariba Shadabi

Research output: A Conference proceeding or a Chapter in BookConference contribution

6 Citations (Scopus)

Abstract

Recent rapid development of computer technology has introduced a data explosion challenge. In addition, data mining and multi agent techniques are known as a very popular approach for dealing with complex datasets. Such a hybrid approach can be considered as an effective approach for the development of intelligent decision support systems in health domain. In this paper we propose an improved data mining and multi agent technique called DMMA, which uses a real time agent mining approach to mine large datasets in a distributed environment. This study found that the processing speed is improved as the result of the multi-agent mining approach, although there can be a corresponding marginal loss of accuracy. This loss of accuracy gap tends to close over time as more data becomes available.
Original languageEnglish
Title of host publication2014 2nd International Conference on Systems and Informatics, ICSAI 2014
Subtitle of host publicationISCAI 2014
EditorsWu Zhang, Qiang Sun, Niansheng Chen
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages241-245
Number of pages5
ISBN (Electronic)9781479954582, 9781479954575
ISBN (Print)9781479954599
DOIs
Publication statusPublished - 15 Nov 2014
Event2nd International Conference on Systems and Informatics: ICSAI 2014 - Shanghai, Shanghai, China
Duration: 15 Nov 201417 Nov 2014

Publication series

Name2014 2nd International Conference on Systems and Informatics, ICSAI 2014

Conference

Conference2nd International Conference on Systems and Informatics
Abbreviated titleICSAI 2014
CountryChina
CityShanghai
Period15/11/1417/11/14

Fingerprint

Decision support systems
Data mining
Explosions
Health
Processing

Cite this

SHARMA, D., & Shadabi, F. (2014). Multi-agents based data mining for intelligent decision support systems. In W. Zhang, Q. Sun, & N. Chen (Eds.), 2014 2nd International Conference on Systems and Informatics, ICSAI 2014: ISCAI 2014 (pp. 241-245). [7009293] (2014 2nd International Conference on Systems and Informatics, ICSAI 2014). USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/icsai.2014.7009293
SHARMA, Dharmendra ; Shadabi, Fariba. / Multi-agents based data mining for intelligent decision support systems. 2014 2nd International Conference on Systems and Informatics, ICSAI 2014: ISCAI 2014. editor / Wu Zhang ; Qiang Sun ; Niansheng Chen. USA : IEEE, Institute of Electrical and Electronics Engineers, 2014. pp. 241-245 (2014 2nd International Conference on Systems and Informatics, ICSAI 2014).
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abstract = "Recent rapid development of computer technology has introduced a data explosion challenge. In addition, data mining and multi agent techniques are known as a very popular approach for dealing with complex datasets. Such a hybrid approach can be considered as an effective approach for the development of intelligent decision support systems in health domain. In this paper we propose an improved data mining and multi agent technique called DMMA, which uses a real time agent mining approach to mine large datasets in a distributed environment. This study found that the processing speed is improved as the result of the multi-agent mining approach, although there can be a corresponding marginal loss of accuracy. This loss of accuracy gap tends to close over time as more data becomes available.",
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SHARMA, D & Shadabi, F 2014, Multi-agents based data mining for intelligent decision support systems. in W Zhang, Q Sun & N Chen (eds), 2014 2nd International Conference on Systems and Informatics, ICSAI 2014: ISCAI 2014., 7009293, 2014 2nd International Conference on Systems and Informatics, ICSAI 2014, IEEE, Institute of Electrical and Electronics Engineers, USA, pp. 241-245, 2nd International Conference on Systems and Informatics, Shanghai, China, 15/11/14. https://doi.org/10.1109/icsai.2014.7009293

Multi-agents based data mining for intelligent decision support systems. / SHARMA, Dharmendra; Shadabi, Fariba.

2014 2nd International Conference on Systems and Informatics, ICSAI 2014: ISCAI 2014. ed. / Wu Zhang; Qiang Sun; Niansheng Chen. USA : IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 241-245 7009293 (2014 2nd International Conference on Systems and Informatics, ICSAI 2014).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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AB - Recent rapid development of computer technology has introduced a data explosion challenge. In addition, data mining and multi agent techniques are known as a very popular approach for dealing with complex datasets. Such a hybrid approach can be considered as an effective approach for the development of intelligent decision support systems in health domain. In this paper we propose an improved data mining and multi agent technique called DMMA, which uses a real time agent mining approach to mine large datasets in a distributed environment. This study found that the processing speed is improved as the result of the multi-agent mining approach, although there can be a corresponding marginal loss of accuracy. This loss of accuracy gap tends to close over time as more data becomes available.

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SHARMA D, Shadabi F. Multi-agents based data mining for intelligent decision support systems. In Zhang W, Sun Q, Chen N, editors, 2014 2nd International Conference on Systems and Informatics, ICSAI 2014: ISCAI 2014. USA: IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 241-245. 7009293. (2014 2nd International Conference on Systems and Informatics, ICSAI 2014). https://doi.org/10.1109/icsai.2014.7009293