A comparative study on clustering-based group scenario summarization in AHP
作者： Akira Suwa , Katsuhiro Honda , Akira Notsu , Tomoe Entani
DOI: 10.1109/SCIS-ISIS.2014.7044690
关键词:
摘要: Group scenario summarization is a useful approach in group decision making. In order to construct intuitive summaries of AHP evaluation weights, this paper adopts several k-means-type clustering methods results. criterion selection level, weights on criteria are summarized into interval for representing the tendencies preferences each cluster. alternative similarities among evaluated by comparing cluster criterion-wise selections with goal merging familiar criteria. Through comparative experiments, applicability method such as noise rejection and k-member discussed.
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