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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8206))

Abstract

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.

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Cheng, S., Shi, Y., Qin, Q., Bai, R. (2013). Swarm Intelligence in Big Data Analytics. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2013. IDEAL 2013. Lecture Notes in Computer Science, vol 8206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41278-3_51

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  • DOI: https://doi.org/10.1007/978-3-642-41278-3_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41277-6

  • Online ISBN: 978-3-642-41278-3

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