タクマ ヒロノリ
Hironori Takuma
田隈 広紀 所属 千葉工業大学 社会システム科学部 プロジェクトマネジメント学科 千葉工業大学 社会システム科学研究科 マネジメント工学専攻 職種 准教授 |
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言語種別 | 英語 |
発行・発表の年月 | 2022/04/20 |
形態種別 | 学術雑誌 |
査読 | 査読あり |
標題 | Solving restriction of Bayesian network in giving domain knowledge by introducing factor nodes |
執筆形態 | 共著 |
掲載誌名 | International Journal of Business Intelligence and Data Mining |
掲載区分 | 国外 |
出版社・発行元 | INDERSCIENCE |
概要 | Bayesian network is a probabilistic inference model that is effective for decision-making in business such as product development. Multiple events are represented as oval nodes and their relationships are drawn as edges among them. However, in order to obtain a sufficient effect, it is necessary to appropriately configure domain knowledge, for example more customer response to the product leads to more clarity of requirements for products. Such domain knowledge is configured as an edge connecting nodes. But in some cases, the constraint of the structure in Bayesian network prevents this configuration. In this study, the authors propose a method to avoid this constraint by introducing the redundant factor nodes generated by applying factor analysis to the data related with domain knowledge. With this approach more domain knowledge can be applied to Bayesian network, and the accuracy of decision-making in business is expected be improved. |