research
∙
06/26/2023
Learn over Past, Evolve for Future: Forecasting Temporal Trends for Fake News Detection
Fake news detection has been a critical task for maintaining the health ...
share
research
∙
05/06/2023
Attacking Pre-trained Recommendation
Recently, a series of pioneer studies have shown the potency of pre-trai...
research
∙
09/19/2022
Improving Fake News Detection of Influential Domain via Domain- and Instance-Level Transfer
Both real and fake news in various domains, such as politics, health, an...
research
∙
06/30/2022
Customized Conversational Recommender Systems
Conversational recommender systems (CRS) aim to capture user's current i...
research
∙
06/26/2022
Memory-Guided Multi-View Multi-Domain Fake News Detection
The wide spread of fake news is increasingly threatening both individual...
research
∙
05/19/2022
Personalized Prompts for Sequential Recommendation
Pre-training models have shown their power in sequential recommendation....
research
∙
05/10/2022
Selective Fairness in Recommendation via Prompts
Recommendation fairness has attracted great attention recently. In real-...
research
∙
05/02/2022
Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion
Most real-world knowledge graphs (KG) are far from complete and comprehe...
research
∙
04/20/2022
Generalizing to the Future: Mitigating Entity Bias in Fake News Detection
The wide dissemination of fake news is increasingly threatening both ind...
research
∙
04/20/2022
User-Centric Conversational Recommendation with Multi-Aspect User Modeling
Conversational recommender systems (CRS) aim to provide highquality reco...
research
∙
03/21/2022
Zoom Out and Observe: News Environment Perception for Fake News Detection
Fake news detection is crucial for preventing the dissemination of misin...
research
∙
03/20/2022
Multi-view Multi-behavior Contrastive Learning in Recommendation
Multi-behavior recommendation (MBR) aims to jointly consider multiple be...
research
∙
01/04/2022
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection
With the explosive growth of the e-commerce industry, detecting online t...
research
∙
01/04/2022
Aligning Domain-specific Distribution and Classifier for Cross-domain Classification from Multiple Sources
While Unsupervised Domain Adaptation (UDA) algorithms, i.e., there are o...
research
∙
01/04/2022
Multi-Representation Adaptation Network for Cross-domain Image Classification
In image classification, it is often expensive and time-consuming to acq...
research
∙
01/04/2022
MDFEND: Multi-domain Fake News Detection
Fake news spread widely on social media in various domains, which lead t...
research
∙
12/31/2021
Neural Hierarchical Factorization Machines for User's Event Sequence Analysis
Many prediction tasks of real-world applications need to model multi-ord...
research
∙
10/21/2021
Personalized Transfer of User Preferences for Cross-domain Recommendation
Cold-start problem is still a very challenging problem in recommender sy...
research
∙
05/31/2021
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising
In recommender systems and advertising platforms, marketers always want ...
research
∙
05/18/2021
Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising
In most real-world large-scale online applications (e.g., e-commerce or ...
research
∙
05/11/2021
Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks
Recently, embedding techniques have achieved impressive success in recom...
research
∙
05/11/2021
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users
Cold-start problems are enormous challenges in practical recommender sys...
research
∙
01/27/2021
Combat Data Shift in Few-shot Learning with Knowledge Graph
Many few-shot learning approaches have been designed under the meta-lear...
research
∙
08/08/2020
Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection
With the explosive growth of e-commerce, online transaction fraud has be...
research
∙
07/12/2020
Graph Factorization Machines for Cross-Domain Recommendation
Recently, graph neural networks (GNNs) have been successfully applied to...
research
∙
11/20/2019
Transfer Learning Toolkit: Primers and Benchmarks
The transfer learning toolkit wraps the codes of 17 transfer learning mo...
research
∙
11/07/2019