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Since there are so many fashion products provided by e-commerce retailers, it is necessary to provide recommendation services to users to minimize information overload. When users look for a product on an e-commerce website, they usually click the product information sequentially. Previous recommenders, such as content-based recommenders and collaborative filtering recommenders, do not consider this important behavioral characteristic. To take advantage of this important characteristic, this study proposes sequence-aware recommenders for fashion product recommendation using a gated recurrent unit (GRU) algorithm. We conducted an experiment using a dataset collected from an e-commerce website of a Korean fashion company. Experimental results show that sequence aware recommenders outperform non-sequence aware recommender, and multiple sequence-based recommenders outperform a single sequence-based recommender because they consider the attributes of fashion products. Finally, we discuss the implications of our study on fashion recommendations and propose further research topics.<\/jats:p>","DOI":"10.1007\/s10660-022-09627-8","type":"journal-article","created":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T19:03:06Z","timestamp":1668193386000},"page":"2733-2753","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Sequence aware recommenders for fashion E-commerce"],"prefix":"10.1007","volume":"24","author":[{"given":"Yang Sok","family":"Kim","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6649-2587","authenticated-orcid":false,"given":"Hyunwoo","family":"Hwangbo","sequence":"additional","affiliation":[]},{"given":"Hee Jun","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Won Seok","family":"Lee","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"key":"9627_CR1","unstructured":"Meena, S. 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