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20212025
most citedOntology Embedding: A Survey of Methods, Applications and Resources

26 citations · 68 across the 15 of their papers we have counts for

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10 papers · 1 filter

cs.AI2025

GR-Agent: Adaptive Graph Reasoning Agent under Incomplete Knowledge

Dongzhuoran Zhou, Yuqicheng Zhu, Xiaxia Wang +5

Large language models (LLMs) achieve strong results on knowledge graph question answering (KGQA), but most benchmarks assume complete knowledge graphs (KGs) where direct supporting…

cs.AI2025

What Breaks Knowledge Graph based RAG? Benchmarking and Empirical Insights into Reasoning under Incomplete Knowledge

Dongzhuoran Zhou, Yuqicheng Zhu, Xiaxia Wang +5

Knowledge Graph-based Retrieval-Augmented Generation (KG-RAG) is an increasingly explored approach for combining the reasoning capabilities of large language models with the struct…

cs.AI2025

Language Models as Ontology Encoders

Hui Yang, Jiaoyan Chen, Yuan He +2

OWL (Web Ontology Language) ontologies which are able to formally represent complex knowledge and support semantic reasoning have been widely adopted across various domains such as…

cs.AI2025

Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness

Dongzhuoran Zhou, Yuqicheng Zhu, Xiaxia Wang +4

Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) is a technique that enhances Large Language Model (LLM) inference in tasks like Question Answering (QA) by retrieving…

cs.AI2024★ 26 cited

Ontology Embedding: A Survey of Methods, Applications and Resources

Jiaoyan Chen, Olga Mashkova, Fernando Zhapa-Camacho +3

Ontologies are widely used for representing domain knowledge and meta data, playing an increasingly important role in Information Systems, the Semantic Web, Bioinformatics and many…

cs.AI2023★ 6 cited

Exploring Large Language Models for Ontology Alignment

Yuan He, Jiaoyan Chen, Hang Dong +1

This work investigates the applicability of recent generative Large Language Models (LLMs), such as the GPT series and Flan-T5, to ontology alignment for identifying concept equiva…

cs.AI2023★ 2 cited

DeepOnto: A Python Package for Ontology Engineering with Deep Learning

Yuan He, Jiaoyan Chen, Hang Dong +4

Integrating deep learning techniques, particularly language models (LMs), with knowledge representation techniques like ontologies has raised widespread attention, urging the need…

cs.AI2022

Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching

Yuan He, Jiaoyan Chen, Hang Dong +3

Ontology Matching (OM) plays an important role in many domains such as bioinformatics and the Semantic Web, and its research is becoming increasingly popular, especially with the a…

cs.AI2022★ 1 cited

Contextual Semantic Embeddings for Ontology Subsumption Prediction

Jiaoyan Chen, Yuan He, Yuxia Geng +3

Automating ontology construction and curation is an important but challenging task in knowledge engineering and artificial intelligence. Prediction by machine learning techniques s…

cs.AI2021

BERTMap: A BERT-based Ontology Alignment System

Yuan He, Jiaoyan Chen, Denvar Antonyrajah +1

Ontology alignment (a.k.a ontology matching (OM)) plays a critical role in knowledge integration. Owing to the success of machine learning in many domains, it has been applied in O…