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 |
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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 27 → 2017 3 29 |
Other
Other | 31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017 |
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Country | Taiwan, Province of China |
City | Taipei |
Period | 17/3/27 → 17/3/29 |
ASJC Scopus subject areas
- Engineering(all)