@article{ART002496972},
author={Kim Chul Jin and Cheon-Woo Jo and Jeong， JiHyun},
title={A Recommendation Technique Based on Offline Product Using Similarity},
journal={Journal of Knowledge Information Technology and Systems},
issn={1975-7700},
year={2019},
volume={14},
number={4},
pages={335-344},
doi={10.34163/jkits.2019.14.4.003}
TY - JOUR
AU - Kim Chul Jin
AU - Cheon-Woo Jo
AU - Jeong， JiHyun
TI - A Recommendation Technique Based on Offline Product Using Similarity
JO - Journal of Knowledge Information Technology and Systems
PY - 2019
VL - 14
IS - 4
PB - Korea Knowledge Information Technology Society
SP - 335
EP - 344
SN - 1975-7700
AB - The online shopping mall can efficiently provide the recommendation product to the user by using the purchase transaction information of the user. However, in the offline store, there is a limit in providing recommended products in real time using information of users or purchase transaction information. Currently, O2O service provision is spreading, but development and research on personalized recommendation service based on offline products are insufficient. In this paper, we propose an architecture for recommending products suitable for users by calculating similarity between products based on offline individual products and online transaction information. We also propose a procedure for deriving a recommendation product among the constituent modules constituting the architecture. The offline individual product is identified through the Beacon sensor, and the user selects the offline product received from the beacon sensor to determine interest. It calculates the similarity based on offline products and online transaction information and provides top-n recommended products to users. We prove the feasibility of the architecture of this study by constructing a system that recommends products that interest the user by calculating the similarity for offline clothing of clothing store. The existing researches recommend brand based on the purchase history of the offline store visited by the user, but in this paper, it is different in terms of providing recommended products for individual products.
KW - Recommendation;Similarity;Offline products;Beacon;Top-n
DO - 10.34163/jkits.2019.14.4.003
ER -
Kim Chul Jin, Cheon-Woo Jo and Jeong， JiHyun. (2019). A Recommendation Technique Based on Offline Product Using Similarity. Journal of Knowledge Information Technology and Systems, 14(4), 335-344.
Kim Chul Jin, Cheon-Woo Jo and Jeong， JiHyun. 2019, "A Recommendation Technique Based on Offline Product Using Similarity", Journal of Knowledge Information Technology and Systems, vol.14, no.4 pp.335-344. Available from: doi:10.34163/jkits.2019.14.4.003
Kim Chul Jin, Cheon-Woo Jo, Jeong， JiHyun "A Recommendation Technique Based on Offline Product Using Similarity" Journal of Knowledge Information Technology and Systems 14.4 pp.335-344 (2019) : 335.
Kim Chul Jin, Cheon-Woo Jo, Jeong， JiHyun. A Recommendation Technique Based on Offline Product Using Similarity. 2019; 14(4), 335-344. Available from: doi:10.34163/jkits.2019.14.4.003
Kim Chul Jin, Cheon-Woo Jo and Jeong， JiHyun. "A Recommendation Technique Based on Offline Product Using Similarity" Journal of Knowledge Information Technology and Systems 14, no.4 (2019) : 335-344.doi: 10.34163/jkits.2019.14.4.003
Kim Chul Jin; Cheon-Woo Jo; Jeong， JiHyun. A Recommendation Technique Based on Offline Product Using Similarity. Journal of Knowledge Information Technology and Systems, 14(4), 335-344. doi: 10.34163/jkits.2019.14.4.003
Kim Chul Jin; Cheon-Woo Jo; Jeong， JiHyun. A Recommendation Technique Based on Offline Product Using Similarity. Journal of Knowledge Information Technology and Systems. 2019; 14(4) 335-344. doi: 10.34163/jkits.2019.14.4.003
Kim Chul Jin, Cheon-Woo Jo, Jeong， JiHyun. A Recommendation Technique Based on Offline Product Using Similarity. 2019; 14(4), 335-344. Available from: doi:10.34163/jkits.2019.14.4.003
Kim Chul Jin, Cheon-Woo Jo and Jeong， JiHyun. "A Recommendation Technique Based on Offline Product Using Similarity" Journal of Knowledge Information Technology and Systems 14, no.4 (2019) : 335-344.doi: 10.34163/jkits.2019.14.4.003
