26 0 0 0 OA 子ども虐待におけるAI 実装:pLSA とベイジアンネットワークを用いた再発事例の検討
- 著者
- 髙岡 昂太 坂本 次郎 北條 大樹 橋本 笑穂 山本 恒雄 北村 光司 櫻井 瑛一 西田 佳史 本村 陽一 K. Takaoka J. Sakamoto D. Hojo E. Hashimoto Yamamoto K. Kitamura E. Sakurai Y. Nishida Y. Motomura
- 雑誌
- SIG-SAI = SIG-SAI
- 巻号頁・発行日
- vol.33, no.5, pp.1-7, 2018-11-22
As the number of reported child abuse cases is increasing, the workload of child welfare social workers is highly escalated. This study aims to find the characteristics of recurrent cases in order to support the social workers. We collected data around the child abuse and neglect from a prefecture database and analyzed it with Probabilistic Latent Semantic Analysis and Bayesian Network modeling. As the result, pLSA showed the four different clusters and Bayesian Network revealed a graphical model about the features of recurrence cases. The Interpretable modeling can be effectively deployed in those child welfare agencies to save children who are suffering from child abuse cases.
1 0 0 0 行動履歴データとライフスタイル調査にもとづく顧客モデル構築技術
- 著者
- 小柴 等 石垣 司 竹中 毅 櫻井 瑛一 本村 陽一
- 出版者
- The Institute of Electrical Engineers of Japan
- 雑誌
- 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and Systems Society (ISSN:03854221)
- 巻号頁・発行日
- vol.133, no.9, pp.1787-1795, 2013-09-01
It becomes increasingly important for service industries to understand customer behavior using large-scale data such as POS data. However, limitations exist in a customer model constructed on the basis of such behavioral data alone. This paper presents how we can construct a customer model on the basis of both large-scale purchase data and lifestyle survey data. It proposes a method that reveals the connection between lifestyle and behavior by deducing lifestyle from behavioral data using Random Forests, a machine learning algorithm. Then, It applies the proposed method to an actual mass merchandizers using questionnaires on lifestyle collected and the customer behavioral data (ID-POS Data). It thereby demonstrates the effectiveness of the proposed method and its possible use in supporting managerial decision-making on critical issues such as product selection.