42 citations · 94 across the 31 of their papers we have counts for
7 papers · 1 filter
Event-based Dynamic Graph Representation Learning for Patent Application Trend Prediction
Tao Zou, Le Yu, Leilei Sun +3
Accurate prediction of what types of patents that companies will apply for in the next period of time can figure out their development strategies and help them discover potential p…
Knowledge-based Multiple Adaptive Spaces Fusion for Recommendation
Meng Yuan, Fuzhen Zhuang, Zhao Zhang +2
Since Knowledge Graphs (KGs) contain rich semantic information, recently there has been an influx of KG-enhanced recommendation methods. Most of existing methods are entirely desig…
Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification
Tao Zou, Le Yu, Junchen Ye +3
Patent classification aims to assign multiple International Patent Classification (IPC) codes to a given patent. Recent methods for automatically classifying patents mainly focus o…
Scaling Sentence Embeddings with Large Language Models
Ting Jiang, Shaohan Huang, Zhongzhi Luan +2
Large language models (LLMs) have recently garnered significant interest. With in-context learning, LLMs achieve impressive results in various natural language tasks. However, the…
Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction
Hao Geng, Deqing Wang, Fuzhen Zhuang +5
Accurate citation count prediction of newly published papers could help editors and readers rapidly figure out the influential papers in the future. Though many approaches are prop…
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph
Chenguang Du, Kaichun Yao, Hengshu Zhu +3
Recent years have witnessed the rapid development of heterogeneous graph neural networks (HGNNs) in information retrieval (IR) applications. Many existing HGNNs design a variety of…
A Survey on Causal Inference for Recommendation
Huishi Luo, Fuzhen Zhuang, Ruobing Xie +4
Causal inference has recently garnered significant interest among recommender system (RS) researchers due to its ability to dissect cause-and-effect relationships and its broad app…