@inproceedings{e4d64269ecc84b50ad4975cadf23fcba,
title = "A Hybrid Recommender System with Implicit Feedbacks in Fashion Retail",
abstract = "In the present paper we propose a hybrid recommender system dealing with implicit feedbacks in the domain of fashion retail. The proposed architecture is based on a collaborative-filtering module taking into account the fact that users feedbacks are not explicit scores about the items, but are obtained through user interactions with the products in terms of number of purchases; moreover, a second module provides a knowledge-based contextual post-filtering, based on both customer-oriented and business-oriented objectives. We finally present a case study where “look-oriented” recommendations have been implemented for a specific fashion retail brand.",
keywords = "Fashion retail, Hybrid architecture, Implicit feedbacks, Recommender systems",
author = "Ilaria Cestari and Luigi Portinale and Riva, \{Pier Luigi\}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 21st International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022 ; Conference date: 28-11-2022 Through 02-12-2022",
year = "2023",
doi = "10.1007/978-3-031-27181-6\_15",
language = "English",
isbn = "9783031271809",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "212--224",
editor = "Agostino Dovier and Angelo Montanari and Andrea Orlandini",
booktitle = "AIxIA 2022 – Advances in Artificial Intelligence - XXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Proceedings",
address = "Germany",
}