A Survey on Bundle Recommendation: Methods, Applications, and Challenges
In recent years, bundle recommendation systems have gained significant attention in both
academia and industry due to their ability to enhance user experience and increase sales by …
academia and industry due to their ability to enhance user experience and increase sales by …
Diversely regularized matrix factorization for accurate and aggregately diversified recommendation
When recommending personalized top-k items to users, how can we recommend them
diversely while satisfying users' needs? Aggregately diversified recommender systems aim …
diversely while satisfying users' needs? Aggregately diversified recommender systems aim …
Calibration-Disentangled Learning and Relevance-Prioritized Reranking for Calibrated Sequential Recommendation
Calibrated recommendation, which aims to maintain personalized proportions of categories
within recommendations, is crucial in practical scenarios since it enhances user satisfaction …
within recommendations, is crucial in practical scenarios since it enhances user satisfaction …
Cold-start Bundle Recommendation via Popularity-based Coalescence and Curriculum Heating
How can we recommend cold-start bundles to users? The cold-start problem in bundle
recommendation is crucial because new bundles are continuously created on the Web for …
recommendation is crucial because new bundles are continuously created on the Web for …
Modeling Bundle Recommendation with Personalized Pattern Analysis
전현식 - 2023 - s-space.snu.ac.kr
Recommender systems aim to suggest a selection of relevant products from the plethora of
ones to users. In recent years, these systems have been indispensable techniques in …
ones to users. In recent years, these systems have been indispensable techniques in …
[PDF][PDF] Diversified and Accurate Recommendations for a Series of Users
J Kim, U Kang - 2024 - kdd2024.kdd.org
ACM Reference Format: Jongjin Kim and U Kang. 2024. Diversified and Accurate
Recommendations for a Series of Users. In Proceedings of 30TH ACM SIGKDD …
Recommendations for a Series of Users. In Proceedings of 30TH ACM SIGKDD …
Accurate Multi-Behavior Sequence-Aware Recommendation via Graph Convolution Networks
D Kim - 2024 - s-space.snu.ac.kr
How can we recommend items to users utilizing multiple types of user behavior data? Multi-
behavior recommender systems use multiple user behavior data to improve the …
behavior recommender systems use multiple user behavior data to improve the …