Family structure attribute estimation method for product recommendation system

Chiaki Doi, Masaji Katagiri, Takashi Araki, Daizo Ikeda, Hiroshi Shigeno

研究成果: Conference contribution

抄録

This paper proposes a method that estimatesconsumer family-structure attributesby focusing on purchasing behavior. The method generatesa relevance model for each product type between family-structure attributes and purchasing histories beforehand based on a consumer panel survey. Random Forest, a machine learning method, is employed to generate the model. The proposed method facilitates provisioning of smart recommendations to the consumer family such as suggesting products that reflectthe family structure attributes of the consumer.

本文言語English
ホスト出版物のタイトルProceedings - 31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ167-173
ページ数7
ISBN(電子版)9781509060283
DOI
出版ステータスPublished - 2017 5 5
イベント31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017 - Taipei, Taiwan, Province of China
継続期間: 2017 3 272017 3 29

Other

Other31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017
CountryTaiwan, Province of China
CityTaipei
Period17/3/2717/3/29

ASJC Scopus subject areas

  • Engineering(all)

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