Affiliations: [a] Dongguan University of Technology, Dongguan, Guangdong, China | [b] South Texas College, McAllen, TX, USA | [c] University of Auckland, Auckland, New Zealand | [d] Nanchang Hangkong University, Nanchang, Jiangxi, China | [e] Department of Computer Science, Indiana University-Purdue University Fort Wayne, Fort Wayne, IN, USA
Correspondence:
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Corresponding author: Tianming Hu, Dongguan University of Technology, Dongguan, Guangdong, China. E-mail: [email protected]
Note: [1] A preliminary version of this work has been published as a short paper in IEEE SMC'09 [34].
Abstract: It is often necessary to combine multiple scores into a joint decision in many real-world applications. To that end, an essential challenge is to build a proper weighted scoring rule, which assigns more weight to the more important scores and derives a final scoring value. In this paper, we first introduce some desirable properties of weighted scoring rules, and then propose a scheme that can incorporate weights into scores in a natural way. In addition, we show our method has overcome some drawbacks of a classic weighted scoring method. Finally, as a case study, we apply these weighted scoring methods to outlier detection to evaluate how much they help solve the ultimate ranking problem.
Keywords: Linear transform, weighted scoring rule, weighting method, ranking
