Biologically Inspired Techniques for Data Mining: A Brief Overview of Particle Swarm Optimization for KDD. Alam
Shafiq, Alam; Gillian, Dobbie; Koh, Yun Sing; Rehman, Saeed
Date
2014-02-02Citation:
Alam, S., Gillian, D., Koh , Y.S., and Rehman, S.U. (2014). Biologically Inspired Techniques for Data Mining: A Brief Overview of Particle Swarm Optimization for KDD. Alam. In Alam, S., Dobbie, G., Koh, Y. S., and Rehman, S. U. (Eds.), Biologically-Inspired Techniques for Knowledge Discovery and Data Mining(Eds.), (p. 1-10). Hershey, PA: Information Science Reference. doi:10.4018/978-1-4666-6078-6.ch001. NOTE: PARTIAL EXTRACT FROM CHAPTERPermanent link to Research Bank record:
https://hdl.handle.net/10652/2959Abstract
Knowledge Discovery and Data (KDD) mining helps uncover hidden knowledge in huge amounts of data. However, recently, different researchers have questioned the capability of traditional KDD techniques to tackle the information extraction problem in an efficient way while achieving accurate results when the amount of data grows. One of the ways to overcome this problem is to treat data mining as an optimization problem. Recently, a huge increase in the use of Swarm Intelligence (SI)-based optimization techniques for KDD has been observed due to the flexibility, simplicity, and extendibility of these techniques to be used for different data mining tasks. In this chapter, the authors overview the use of Particle Swarm Optimization (PSO), one of the most cited SI-based techniques in three different application areas of KDD, data clustering, outlier detection, and recommender systems. The chapter shows that there is a tremendous potential in these techniques to revolutionize the process of extracting knowledge from big data using these techniques
Keywords:
data mining, databases, particle swarm optimization, information retrieval, library and information scienceANZSRC Field of Research:
080109 Pattern Recognition and Data Mining, 080704 Information Retrieval and Web SearchCopyright Holder:
IGI GlobalCopyright Notice:
Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.Available Online at:
http://www.igi-global.com/chapter/biologically-inspired-techniques-for-data-mining/110452http://www.irma-international.org/chapter/biologically-inspired-techniques-for-data-mining/110452/