@inproceedings{193afc12470241a9b7228d5ce94586d3,
title = "Sequential pattern mining for e-commerce recommender system",
abstract = "Recommender system is one of the strategies carried out by e-commerce to increase their users' satisfaction. In this paper, we implement sequence pattern mining for recommender system in e-commerce domain. We perform the PrefixSpan algorithm to mine the frequent patterns. The frequent patterns generate the suitable rules for the recommender system. The experiments reported in this paper utilize the datasets from two different marketplaces in Indonesia. The best performance of recommendation model is obtained when applying the rules derived from the product category with minimum confidence of 0.5.",
keywords = "e-Commerce, PrefixSpan, Recommender Systems, Sequential Pattern Mining",
author = "Ridho Trivonanda and Rahmad Mahendra and Indra Budi and Hidayat, {Rani Aulia}",
note = "Funding Information: The authors gratefully acknowledge the support of Universitas Indonesia through grant {"}Hibah Publikasi Terindeks Internasional (PUTI) Q2 year 2020 no NKB- 1473/UN2.RST/HKP.05.00/2020. Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 12th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020 ; Conference date: 17-10-2020 Through 18-10-2020",
year = "2020",
month = oct,
day = "17",
doi = "10.1109/ICACSIS51025.2020.9263192",
language = "English",
series = "2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "393--398",
booktitle = "2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020",
address = "United States",
}