research
∙
02/05/2023
Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction
In this study, we propose a novel SeqMF model to solve the problem of pr...
share
research
∙
01/08/2023
Mitigating Human and Computer Opinion Fraud via Contrastive Learning
We introduce the novel approach towards fake text reviews detection in c...
research
∙
12/12/2022
Tensor-based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations
Self-attentive transformer models have recently been shown to solve the ...
research
∙
05/10/2022
Tensor-based Collaborative Filtering With Smooth Ratings Scale
Conventional collaborative filtering techniques don't take into consider...
research
∙
05/09/2022
Are Quantum Computers Practical Yet? A Case for Feature Selection in Recommender Systems using Tensor Networks
Collaborative filtering models generally perform better than content-bas...
research
∙
04/22/2022
MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering
Knowledge Graphs (KGs) are symbolically structured storages of facts. Th...
research
∙
04/11/2021
Dynamic Modeling of User Preferences for Stable Recommendations
In domains where users tend to develop long-term preferences that do not...
research
∙
08/15/2020
Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks
We introduce a simple autoencoder based on hyperbolic geometry for solvi...
research
∙
07/27/2018
Revealing the Unobserved by Linking Collaborative Behavior and Side Knowledge
We propose a tensor-based model that fuses a more granular representatio...
research
∙
02/18/2018
HybridSVD: When Collaborative Information is Not Enough
We propose a hybrid algorithm for top-n recommendation task that allows ...
research
∙
07/14/2016
Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks
Conventional collaborative filtering techniques treat a top-n recommenda...
research
∙
03/19/2016