Purchasing Behavior Prediction Model for Real Stores Considering Product Cluster and Time-series Patterns

Author:

Sakuma Yuiko1,Yoshida Masahiro1,Nishi Hiroaki2

Affiliation:

1. Graduate School of Science and Technology, Keio University

2. Department of System Design, Faculty of Science and Technology, Keio University

Publisher

Institute of Electrical Engineers of Japan (IEE Japan)

Subject

Electrical and Electronic Engineering

Reference30 articles.

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2. (2) K. Swearingen and R. Sinha : “Beyond Algorithms : An HCI Perspective on Recommender Systems”, ACM SIGIR Workshop on Recommender Systems, pp. 1-11 (2001)

3. (3) A. Sharma, J. M. Hofman, and D. J. Watts : “Estimating the causal impact of recommendation systems from observational data”, Proceedings of the Sixteenth ACM Conference on Economics and Computation, pp. 453-470 (2015)

4. (4) C. A. Gomez-Uribe and N. Hunt : “The netflix recommender system: Algorithms, business value, and innovation”, ACM Transactions on Management Information Systems, Vol. 6, No. 4, pp. 1-19 (2015)

5. (5) Ministry of Economy, Trade and Industry : “Cashless vision” (in Japanese) [Online]. Available: https://www.meti.go.jp/report/whitepaper/data/pdf/20180411002_01.pdf [Accessed: 1 June 2020]

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