150 citations · 177 across the 8 of their papers we have counts for
12 papers
OntoZSL: Ontology-enhanced Zero-shot Learning
Yuxia Geng, Jiaoyan Chen, Zhuo Chen +5
Zero-shot Learning (ZSL), which aims to predict for those classes that have never appeared in the training data, has arisen hot research interests. The key of implementing ZSL is t…
Logic-guided Semantic Representation Learning for Zero-Shot Relation Classification
Juan Li, Ruoxu Wang, Ningyu Zhang +3
Relation classification aims to extract semantic relations between entity pairs from the sentences. However, most existing methods can only identify seen relation classes that occu…
FedE: Embedding Knowledge Graphs in Federated Setting
Mingyang Chen, Wen Zhang, Zonggang Yuan +2
Knowledge graphs (KGs) consisting of triples are always incomplete, so it's important to do Knowledge Graph Completion (KGC) by predicting missing triples. Multi-Source KG is a com…
Ontology-guided Semantic Composition for Zero-Shot Learning
Jiaoyan Chen, Freddy Lecue, Yuxia Geng +2
Zero-shot learning (ZSL) is a popular research problem that aims at predicting for those classes that have never appeared in the training stage by utilizing the inter-class relatio…
Neural Entity Summarization with Joint Encoding and Weak Supervision
Junyou Li, Gong Cheng, Qingxia Liu +4
In a large-scale knowledge graph (KG), an entity is often described by a large number of triple-structured facts. Many applications require abridged versions of entity descriptions…
Generative Adversarial Zero-shot Learning via Knowledge Graphs
Yuxia Geng, Jiaoyan Chen, Zhuo Chen +4
Zero-shot learning (ZSL) is to handle the prediction of those unseen classes that have no labeled training data. Recently, generative methods like Generative Adversarial Networks (…