Browse > Article
http://dx.doi.org/10.9728/dcs.2017.18.8.1561

Pet Shop Recommendation System based on Implicit Feedback  

Choi, Heeyoul (School of Computer Science and Electrical Engineering, Handong Global University)
Kang, Yunhee (Division of Information & Communication, Baekseok University)
Kang, Myungju (Division of BigData Business, Triniti, Inc.)
Publication Information
Journal of Digital Contents Society / v.18, no.8, 2017 , pp. 1561-1566 More about this Journal
Abstract
Due to the advances in machine learning and artificial intelligence technologies, many new services have become available. Among such services, recommendation systems have already been successfully applied to commercial services and made profits as in online shopping malls. Most recommendation algorithms in commercial services are based on content analysis or explicit feedback rates as in movie recommendations. However, many online shopping malls have difficulties in content analysis or are lacking explicit feedbacks on their items, which results in no recommendation system for their items. Even for such service systems, user log data is easily available, and if recommendations are possible with such log data, the quality of their service can be improved. In this paper, we extract implicit feedback like click information for items from log data and provide a recommendation system based on the implicit feedback. The proposed system is applied to a real in-service online shopping mall.
Keywords
Machine learning; Recommendation systems; Implicit feedback; Click information on items;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Y. LeCun, Y. Bengio, and G. Hinton, "Deep learning," Nature, Vol. 521, No. 7553, pp. 436-444, May 2015.   DOI
2 D. Bahdanau, K. Cho, and Y. Bengio, "Neural machine translation by jointly learning to align and translate," in Proceeding of the International Conference on Learning Representations, San Diego: CA, May 2015.
3 K. Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhutdinov, R. Zemel, and Y. Bengio, "Show, attend and tell: Neural Image Caption Generation with Visual Attention," in Proceeding of the International Conference on Machine Learning, Lille: France, pp. 2048-2057, July 2015.
4 Y. Koren, R. Bell, and C. Volinsky, "Matrix factorization techniques for recommender systems," IEEE Computer Society, Vol. 42, No. 8, pp.30-37, August 2009.
5 H. R. Choi, B. I. An, and G. I. Chung, "Mobile Context Based User Behavior Pattern Inference and Restaurant Recommendation Model," The Journal of Digital Contents Society, Vol.18, No. 3, pp.535-542, June 2017.   DOI
6 H. J. Kim and S. Y. Chung, "A Recommender System Using Factorization Machine," The Journal of Digital Contents Society, Vol. 18, No. 4, pp.707-717, July 2017.   DOI
7 Y. Hu, Y. Koren, and C. Volinsky, "Collaborative filtering for implicit feedback datasets," in Proceeding of the International Conference on Data Mining, Pisa: Italy, pp. 263-272, December 2008.