A survey on session-based recommender systems

S Wang, L Cao, Y Wang, QZ Sheng, MA Orgun… - ACM Computing …, 2021 - dl.acm.org
Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …

Evaluation of session-based recommendation algorithms

M Ludewig, D Jannach - User Modeling and User-Adapted Interaction, 2018 - Springer
Recommender systems help users find relevant items of interest, for example on e-
commerce or media streaming sites. Most academic research is concerned with approaches …

A survey on stream-based recommender systems

M Al-Ghossein, T Abdessalem, A Barré - ACM computing surveys (CSUR …, 2021 - dl.acm.org
Recommender Systems (RS) have proven to be effective tools to help users overcome
information overload, and significant advances have been made in the field over the past …

Meta-prod2vec: Product embeddings using side-information for recommendation

F Vasile, E Smirnova, A Conneau - … of the 10th ACM conference on …, 2016 - dl.acm.org
We propose Meta-Prod2vec, a novel method to compute item similarities for
recommendation that leverages existing item metadata. Such scenarios are frequently …

Word2vec applied to recommendation: Hyperparameters matter

H Caselles-Dupré, F Lesaint… - Proceedings of the 12th …, 2018 - dl.acm.org
Skip-gram with negative sampling, a popular variant of Word2vec originally designed and
tuned to create word embeddings for Natural Language Processing, has been used to …

An attribute-driven mirror graph network for session-based recommendation

S Lai, E Meng, F Zhang, C Li, B Wang… - Proceedings of the 45th …, 2022 - dl.acm.org
Session-based recommendation (SBR) aims to predict a user's next clicked item based on
an anonymous yet short interaction sequence. Previous SBR models, which rely only on the …

Long-tail session-based recommendation

S Liu, Y Zheng - Proceedings of the 14th ACM conference on …, 2020 - dl.acm.org
Session-based recommendation focuses on the prediction of user actions based on
anonymous sessions and is a necessary method in the lack of user historical data. However …

Multi-view enhanced graph attention network for session-based music recommendation

D Wang, X Zhang, Y Yin, D Yu, G Xu… - ACM Transactions on …, 2023 - dl.acm.org
Traditional music recommender systems are mainly based on users' interactions, which limit
their performance. Particularly, various kinds of content information, such as metadata and …

Session-based recommender systems

D Jannach, M Quadrana, P Cremonesi - Recommender Systems …, 2022 - Springer
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A survey on incremental update for neural recommender systems

P Zhang, S Kim - arXiv preprint arXiv:2303.02851, 2023 - arxiv.org
Recommender Systems (RS) aim to provide personalized suggestions of items for users
against consumer over-choice. Although extensive research has been conducted to address …