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Eコマースの購入ログを用いたペットフードと犬の疾患の関連性分析

笹谷 奈翁美, 岸田 滋史*, 菊地 了*, 山口 修司, 田島 玲 (*アニコム ホールディングス)

2020年度 人工知能学会全国大会 (第34回) (JSAI 2020), 2020/6

Category:

Machine Learning Data Science Misc.

Abstract:
In this study, we investigated the effects of pet foods on pet’s health using five datasets: tens of thousands of questionnaire answers from pet insurance members, claim data from pet insurance members, the more than millions purchase histories of pet foods on the e-commerce site, ingredients of pet foods, and categories of ingredients. Since there is no information about the diseases on the e-commerce site, we used specific purchase activities as alternative indicators of sign of disease, and built a dataset with positive/negative labels based on purchase histories of e- commerce site. This time, as an example of the application of big data using alternative indicators, we investigated the ingredients of pet food that affect allergic diseases in dogs, and identified the ingredients that affected those disease.

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