no code implementations • EMNLP 2020 • Zhichun Wang, Jinjian Yang, Xiaoju Ye
Recently, a number of embedding-based approaches for KG alignment have been proposed and achieved promising results.
no code implementations • 9 Mar 2020 • Xianpei Han, Zhichun Wang, Jiangtao Zhang, Qinghua Wen, Wenqi Li, Buzhou Tang, Qi. Wang, Zhifan Feng, Yang Zhang, Yajuan Lu, Haitao Wang, Wenliang Chen, Hao Shao, Yubo Chen, Kang Liu, Jun Zhao, Taifeng Wang, Kezun Zhang, Meng Wang, Yinlin Jiang, Guilin Qi, Lei Zou, Sen Hu, Minhao Zhang, Yinnian Lin
Knowledge graph models world knowledge as concepts, entities, and the relationships between them, which has been widely used in many real-world tasks.
no code implementations • IJCNLP 2019 • Lan Jiang, Shuhan Hu, Mingyu Huang, Zhichun Wang, Jinjian Yang, Xiaoju Ye, Wei Zheng
Massive Open Online Courses (MOOCs) have developed rapidly and attracted large number of learners.
1 code implementation • EMNLP 2018 • Zhichun Wang, Qingsong Lv, Xiaohan Lan, Yu Zhang
Embeddings can be learned from both the structural and attribute information of entities, and the results of structure embedding and attribute embedding are combined to get accurate alignments.
Ranked #5 on
Entity Alignment
on YAGO-WIKI50K
no code implementations • WS 2018 • Yanrong Wu, Zhichun Wang
Knowledge Graph (KG) embedding projects entities and relations into low dimensional vector space, which has been successfully applied in KG completion task.
no code implementations • 24 Dec 2015 • Zhichun Wang, Juanzi Li
Recently, several large-scale RDF knowledge bases have been built and applied in many knowledge-based applications.