• Title/Summary/Keyword: KASA-PSO

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An Empirical Analysis Approach to Investigating Effectiveness of the PSO-based Clustering Method for Scholarly Papers Supported by the Research Grant Projects (개선된 PSO방법에 의한 학술연구조성사업 논문의 효과적인 분류 방법과 그 효과성에 관한 실증분석)

  • Lee, Kun-Chang;Seo, Young-Wook;Lee, Dae-Sung
    • Knowledge Management Research
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    • v.10 no.4
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    • pp.17-30
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    • 2009

  • This study is concerned with suggesting a new clustering algorithm to evaluate the value of papers which were supported by research grants by Korea Research Fund (KRF). The algorithm is based on an extended version of a conventional PSO (Particle Swarm Optimization) mechanism. In other words, the proposed algorithm is based on integration of k-means algorithm and simulated annealing mechanism, named KASA-PSO. To evaluate the robustness of KASA-PSO, its clustering results are evaluated by research grants experts working at KRF. Empirical results revealed that the proposed KASA-PSO clustering method shows improved results than conventional clustering method.

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