Collaborative Filtering
431 papers with code • 3 benchmarks • 6 datasets
Libraries
Use these libraries to find Collaborative Filtering models and implementations
MovieLens
Gowalla
Yelp2018
Latest papers
Graph Neural Controlled Differential Equations For Collaborative Filtering
However, we argue that weight control is critical for neural ODE-based methods.
Diffusion Models in Recommendation Systems: A Survey
In this survey paper, we present and propose a taxonomy on past research papers in recommender systems that utilize diffusion models.
RecLM: Recommendation Instruction Tuning
hkuds/reclm
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Modern recommender systems aim to deeply understand users' complex preferences through their past interactions.
Unlocking the Hidden Treasures: Enhancing Recommendations with Unlabeled Data
Implementing the PNN paradigm is, however, technically challenging because: (1) it is difficult to classify unlabeled data into neutral or negative in the absence of supervised signals; (2) there does not exist any loss function that can handle set-level triple-wise ranking relationships.
MixRec: Heterogeneous Graph Collaborative Filtering
hkuds/mixrec
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For modern recommender systems, the use of low-dimensional latent representations to embed users and items based on their observed interactions has become commonplace.
STAIR: Manipulating Collaborative and Multimodal Information for E-Commerce Recommendation
yhhe2004/stair
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In order to combine the two distinct types of information, some additional challenges are encountered: 1) Modality erasure: Vanilla graph convolution, which proves rather useful in collaborative filtering, however erases multimodal information; 2) Modality forgetting: Multimodal information tends to be gradually forgotten as the recommendation loss essentially facilitates the learning of collaborative information.
Recommender systems and reinforcement learning for human-building interaction and context-aware support: A text mining-driven review of scientific literature
The indoor environment significantly impacts human health and well-being; enhancing health and reducing energy consumption in these settings is a central research focus.
Language-Model Prior Overcomes Cold-Start Items
awslabs/language-model-prior-4-item-cold-start
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Existing solutions for the cold-start problem, such as content-based recommenders and hybrid methods, leverage item metadata to determine item similarities.
Co-clustering for Federated Recommender System
In this paper, we delve into the inefficiencies of the K-Means method in client grouping, attributing failures due to the high dimensionality as well as data sparsity occurring in FRS, and propose CoFedRec, a novel Co-clustering Federated Recommendation mechanism, to address clients heterogeneity and enhance the collaborative filtering within the federated framework.
Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation
Adversarial Collaborative Filtering (ACF), which typically applies adversarial perturbations at user and item embeddings through adversarial training, is widely recognized as an effective strategy for enhancing the robustness of Collaborative Filtering (CF) recommender systems against poisoning attacks.
