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Collaborative Filtering

60 papers with code · Miscellaneous

Collaborative filtering is a recommendation system that uses user's past behaviour (items previously purchased or selected and/or numerical ratings given to those items) as well as similar decisions made by other users. This model is then used to predict items (or ratings for items) that the user may have an interest in.

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Latest papers with code

Coupled Variational Recurrent Collaborative Filtering

11 Jun 2019song3134/CVRCF

To bridge the gap, in this paper, we propose a Coupled Variational Recurrent Collaborative Filtering (CVRCF) framework based on the idea of Deep Bayesian Learning to handle the streaming recommendation problem.

COLLABORATIVE FILTERING

1
11 Jun 2019

Towards Amortized Ranking-Critical Training for Collaborative Filtering

10 Jun 2019samlobel/RaCT_CF

In this paper we investigate new methods for training collaborative filtering models based on actor-critic reinforcement learning, to directly optimize the non-differentiable quality metrics of interest.

COLLABORATIVE FILTERING LEARNING-TO-RANK

1
10 Jun 2019

On the Effectiveness of Low-rank Approximations for Collaborative Filtering compared to Neural Networks

30 May 2019FlorianWilhelm/lrann

Even in times of deep learning, low-rank approximations by factorizing a matrix into user and item latent factors continue to be a method of choice for collaborative filtering tasks due to their great performance.

COLLABORATIVE FILTERING

3
30 May 2019

Evaluating recommender systems for AI-driven data science

22 May 2019EpistasisLab/pennai

The recommender system learns online as results are generated.

COLLABORATIVE FILTERING

81
22 May 2019

Neural Graph Collaborative Filtering

20 May 2019xiangwang1223/neural_graph_collaborative_filtering

Further analysis verifies the importance of embedding propagation for learning better user and item representations, justifying the rationality and effectiveness of NGCF.

COLLABORATIVE FILTERING

119
20 May 2019

Compositional Coding for Collaborative Filtering

9 May 20193140102441/CCCF

However, CF with binary codes naturally suffers from low accuracy due to limited representation capability in each bit, which impedes it from modeling complex structure of the data.

COLLABORATIVE FILTERING

1
09 May 2019

On the Difficulty of Evaluating Baselines: A Study on Recommender Systems

4 May 2019srendle/libfm

Numerical evaluations with comparisons to baselines play a central role when judging research in recommender systems.

COLLABORATIVE FILTERING

1,129
04 May 2019

Relational Collaborative Filtering:Modeling Multiple Item Relations for Recommendation

29 Apr 2019XinGla/RCF

In this work, we propose Relational Collaborative Filtering (RCF), a general framework to exploit multiple relations between items in recommender system.

COLLABORATIVE FILTERING

18
29 Apr 2019

A Neural Influence Diffusion Model for Social Recommendation

20 Apr 2019PeiJieSun/diffnet

The key idea of our proposed model is that we design a layer-wise influence propagation structure to model how users' latent embeddings evolve as the social diffusion process continues.

COLLABORATIVE FILTERING

25
20 Apr 2019

Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems

25 Mar 2019echo740/DANSER-WWW-19

Social recommendation leverages social information to solve data sparsity and cold-start problems in traditional collaborative filtering methods.

COLLABORATIVE FILTERING

15
25 Mar 2019