The ability of recommending cold items (that have no behavior history) is a core strength of multimedia recommendation compared with behavior-only collaborative ...

Oct 12, 2020 · To learn effective item representation, a key challenge lies in the discrepancy between training and testing, since the cold items only exist in the testing ...

Oct 12, 2020 · We highlight the training-testing discrepancy for cold item representation in multimedia recommendation. • We propose a novel generic learning ...

Cold-start Item Recommendation. Without enough historic interaction, traditional recommender systems based on collaborative filtering will fail to infer ...

Apr 22, 2024 · In this paper, we propose a domain/data-agnostic item representation learning framework for cold-start recommendations, naturally equipped with multimodal ...

Apr 22, 2024 · In this paper, we propose a domain/data-agnostic item representation learning framework for cold-start recommendations, naturally equipped with ...

This repository contains a curated list of papers on cold-start recommendations, which are sorted by their published years.

Missing: Multimedia | Show results with:Multimedia

Multi-Task Pairwise Ranking (MTPR) aims to address the discrepancy during the training process of cold-start recommendation.

Existing cold-start recommendation methods often adopt item-level alignment strategies to align the content feature and the collaborative feature of warm items ...