Results 21 to 30 of about 2,553,529 (294)
Cold-start Sequential Recommendation via Meta Learner
, 2021 This paper explores meta-learning in sequential recommendation to alleviate the item cold-start problem. Sequential recommendation aims to capture user's dynamic preferences based on historical behavior sequences and acts as a key component of most ...
Zheng, Yujia +3 more
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Recommendations from Cold Starts in Big Data [PDF]
Proceedings of the 4th International Conference on Internet of Things, Big Data and Security, 2019 AbstractThis paper examines the challenging problem of new user cold starts in subset labelled and extremely sparsely labelled big data. We introduce a new Isle of Wight Supply Chain (IWSC) dataset demonstrating these characteristics. We also introduce a new technique addressing these challenges, the Transitive Semantic Relationships (TSR) model, which
David Ralph +3 more
openaire +3 more sources
Contrastive Collaborative Filtering for Cold-Start Item Recommendation
, 2023 The cold-start problem is a long-standing challenge in recommender systems. As a promising solution, content-based generative models usually project a cold-start item's content onto a warm-start item embedding to capture collaborative signals from item ...
Zhang, Lilin, Zhou, Zhihui, Yang, Ning
core +1 more source
Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder [PDF]
, 2022 Embedding & MLP has become a paradigm for modern large-scale recommendation system. However, this paradigm suffers from the cold-start problem which will seriously compromise the ecological health of recommendation systems.
Ren, Yi +9 more
core +1 more source
Survey on Solving Cold Start Problem in Recommendation Systems [PDF]
Jisuanji kexue yu tansuoRecommender systems provide important functions in areas such as dealing with data overload, providing personalized consulting services, and assisting clients in investment decisions. However, the cold start problem in recommender systems has always been
MAO Qian, XIE Weicheng, QIAO Yitian, HUANG Xiaolong, DONG Gang
doaj +1 more source
Hybrid Deep Framework for Group Event Recommendation
IEEE Access, 2020 Group recommender systems suggesting items for a group of users have received many attentions recently. Some aggregation-based and model-based group recommendation methods have been proposed.
Ruichang Li +3 more
doaj +1 more source
Addressing the Cold-Start Problem in Personalized Flight Ticket Recommendation
IEEE Access, 2019 With the rapid development of the tourist industry, an increasing number of passengers book flight tickets through online travel agencies. When searching for a flight ticket online, users are overwhelmed by the choice on offer.
Qi Gu, Jian Cao, Yafeng Zhao, Yudong Tan
doaj +1 more source
IT Journal Research and Development, 2021 Increasing number of internet users today, the use of e-commerce becomes a very vital need. One of the keys that holds the success of the e-commerce system is the recommendation system.
Nasy`an Taufiq Al Ghifari +2 more
doaj +1 more source
Normalization-based neighborhood model for cold start problem in recommendation system [PDF]
, 2019 Existing approaches for Recommendation Systems (RS) are mainly based on users’ past knowledge and the more popular techniques such as the neighborhood models focus on finding similar users in making recommendations.
Zahid, Aafaq +5 more
core +1 more source
Generative Adversarial Zero-Shot Learning for Cold-Start News Recommendation
, 2022 News recommendation models extremely rely on the interactive information between users and news articles to personalize the recommendation. Therefore, one of their most serious challenges is the cold-start problem (CSP).
Zhang, Xiangliang, Alshehri, Manal A.
core +2 more sources