Swarm intelligence in big data analytics

Shi Cheng, Yuhui Shi, Quande Qin, Ruibin Bai

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

40 Citations (Scopus)


This paper analyses the difficulty of big data analytics problems and the potential of swarm intelligence solving big data analytics problems. Nowadays, the big data analytics has attracted more and more attentions, which is required to manage immense amounts of data quickly. However, current researches mainly focus on the amount of data. In this paper, the other three properties of big data analytics, which include the high dimensionality of data, the dynamical change of data, and the multi-objective of problems, are discussed. Swarm intelligence, which works with a population of individuals, is a collection of nature-inspired searching techniques. It has effectively solved many large-scale, dynamical, and multi-objective problems. Based on the combination of swarm intelligence and data mining techniques, we can have better understanding of the big data analytics problems, and designing more effective algorithms to solve real-world big data analytics problems.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning - 14th International Conference, IDEAL 2013, Proceedings
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783642412776
Publication statusPublished - 2013
Event14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013 - Hefei, China
Duration: 20 Oct 201323 Oct 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8206 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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