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Simplified Swarm Optimization for Life Log Data Mining

Simplified Swarm Optimization for Life Log Data Mining
학술지명 Lecture Notes in Electrical Engineering ISSN 1876-1100
SCI 유무 없음 게재연월 2012-01 Vol. 107 No. 1
표준화된 순위정보영향력지수 - IF - Citation -

Simplified Swarm Optimization for Life Log Data Mining
국제공동연구 University of Technology Sydney(Australia),
저자 Changseok Bae, Wei-Chang Yeh and Yuk Ying Chung
초록
This paper proposes a new evolutionary algorithm for life log data mining. The proposed algorithm is based on the particle swarm optimization. The proposed algorithm focuses on three goals such as size reduction of data set, fast convergence, and higher classification accuracy. After executing feature selection method, we employ a method to reduce the size of data set. In order to reduce the processing time, we introduce a simple rule to determine the next movements of the particles. We have applied the proposed algorithm to the UCI data set. The experimental results ascertain that the proposed algorithm show better performance compared to the conventional classification algorithms such as PART, KNN, Classification Tree and Naïve Bayes.
keyword Life log, Particle Swarm Optimization, Simplified Swarm Optimization

Simplified Swarm Optimization for Life Log Data Mining
과제명 인간 교감 신개념 UI 기반 인터랙션 기술
연구기관 한국전자통신연구원 연구책임자 손승원