@phdthesis{oai:doshisha.repo.nii.ac.jp:00001285,
 author = {谷岡, 健資 and Tanioka, Kensuke},
 month = {2016-06-24, 2017-03-09},
 note = {本論文は，非対称非類似度データに対するクラスタリング法と非対称多次元尺度構成法の同時分析法である制約付き非対称多次元尺度構成法に関する研究である．本手法の特徴として，対象間の非対称性を表現するモデルではなく，クラスター間の非対称性を表現するモデルであることが挙げられる．具体的には展開法やスライドベクターモデル，丘陵モデル，半径モデルに基づく制約付き非対称多次元尺度構成法を提案した．, In this paper, we dealt with constrained analysis of asymmetric dissimilarity data by using MDS and clustering. As a feature of these methods, these models describe not asymmetric relations between objects but those between clusters based on various models. Concretely, we proposed four kinds of constrained asymmetric methods based on Unfolding, slide-vector model, hill-climbing model and radius model, respectively. In addition to that, relations between these methods are also shown based on these objective functions., application/pdf},
 title = {Constrained analysis of asymmetric dissimilarity data by using both MDS and clustering},
 year = {},
 yomi = {タニオカ, ケンスケ}
}