2 citations · 4 across the 6 of their papers we have counts for
7 papers
Beyond Completion: A Foundation Model for General Knowledge Graph Reasoning
Yin Hua, Zhiqiang Liu, Mingyang Chen +6
In natural language processing (NLP) and computer vision (CV), the successful application of foundation models across diverse tasks has demonstrated their remarkable potential. How…
PKGM: A Pre-trained Knowledge Graph Model for E-commerce Application
Wen Zhang, Chi-Man Wong, Ganqinag Ye +4
In recent years, knowledge graphs have been widely applied as a uniform way to organize data and have enhanced many tasks requiring knowledge. In online shopping platform Taobao, w…
Improving Knowledge Graph Representation Learning by Structure Contextual Pre-training
Ganqiang Ye, Wen Zhang, Zhen Bi +3
Representation learning models for Knowledge Graphs (KG) have proven to be effective in encoding structural information and performing reasoning over KGs. In this paper, we propose…
Complexity-Optimized Sparse Bayesian Learning for Scalable Classification Tasks
Jiahua Luo, Chi-Man Wong, Chi-Man Vong
Sparse Bayesian Learning (SBL) constructs an extremely sparse probabilistic model with very competitive generalization. However, SBL needs to invert a big covariance matrix with co…
Billion-scale Pre-trained E-commerce Product Knowledge Graph Model
Wen Zhang, Chi-Man Wong, Ganqiang Ye +3
In recent years, knowledge graphs have been widely applied to organize data in a uniform way and enhance many tasks that require knowledge, for example, online shopping which has g…
Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graph
Chi-Man Wong, Fan Feng, Wen Zhang +7
Conversational Recommender Systems (CRSs) in E-commerce platforms aim to recommend items to users via multiple conversational interactions. Click-through rate (CTR) prediction mode…
Neural Abstractive Summarization with Structural Attention
Tanya Chowdhury, Sachin Kumar, Tanmoy Chakraborty
Attentional, RNN-based encoder-decoder architectures have achieved impressive performance on abstractive summarization of news articles. However, these methods fail to account for…