223 citations · 232 across the 12 of their papers we have counts for
12 papers
Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation
Jin-Duk Park, Siqing Li, Xin Cao +1
The multi-criteria (MC) recommender system, which leverages MC rating information in a wide range of e-commerce areas, is ubiquitous nowadays. Surprisingly, although graph neural n…
Quantifying the Optimization and Generalization Advantages of Graph Neural Networks Over Multilayer Perceptrons
Wei Huang, Yuan Cao, Haonan Wang +2
Graph neural networks (GNNs) have demonstrated remarkable capabilities in learning from graph-structured data, often outperforming traditional Multilayer Perceptrons (MLPs) in nume…
Exploiting Correlations Between Contexts and Definitions with Multiple Definition Modeling
Linhan Zhang, Qian Chen, Wen Wang +4
Definition modeling is an important task in advanced natural language applications such as understanding and conversation. Since its introduction, it focus on generating one defini…
Centrality-Based Node Feature Augmentation for Robust Network Alignment
Jin-Duk Park, Cong Tran, Won-Yong Shin +1
Network alignment (NA) is the task of discovering node correspondences across multiple networks. Although NA methods have achieved remarkable success in a myriad of scenarios, thei…
Weighted Sampling for Masked Language Modeling
Linhan Zhang, Qian Chen, Wen Wang +5
Masked Language Modeling (MLM) is widely used to pretrain language models. The standard random masking strategy in MLM causes the pre-trained language models (PLMs) to be biased to…
Grad-Align+: Empowering Gradual Network Alignment Using Attribute Augmentation
Jin-Duk Park, Cong Tran, Won-Yong Shin +1
Network alignment (NA) is the task of discovering node correspondences across different networks. Although NA methods have achieved remarkable success in a myriad of scenarios, the…
Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System
Ding Zou, Wei Wei, Xian-Ling Mao +4
Knowledge graph (KG) plays an increasingly important role in recommender systems. Recently, graph neural networks (GNNs) based model has gradually become the theme of knowledge-awa…
On the Power of Gradual Network Alignment Using Dual-Perception Similarities
Jin-Duk Park, Cong Tran, Won-Yong Shin +1
Network alignment (NA) is the task of finding the correspondence of nodes between two networks based on the network structure and node attributes. Our study is motivated by the fac…
Off-Dynamics Inverse Reinforcement Learning from Hetero-Domain
Yachen Kang, Jinxin Liu, Xin Cao +1
We propose an approach for inverse reinforcement learning from hetero-domain which learns a reward function in the simulator, drawing on the demonstrations from the real world. The…
MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction
Linhan Zhang, Qian Chen, Wen Wang +5
Keyphrase extraction (KPE) automatically extracts phrases in a document that provide a concise summary of the core content, which benefits downstream information retrieval and NLP…
Edgeless-GNN: Unsupervised Representation Learning for Edgeless Nodes
Yong-Min Shin, Cong Tran, Won-Yong Shin +1
We study the problem of embedding edgeless nodes such as users who newly enter the underlying network, while using graph neural networks (GNNs) widely studied for effective represe…
Improved Online Wilson Score Interval Method for Community Answer Quality Ranking
Xin Cao
In this paper, a fast and easy-to-deploy method with a strong interpretability for community answer quality ranking is proposed. This method is improved based on the Wilson score i…