activity
20182023
most citedKG-BERT: BERT for Knowledge Graph Completion

382 citations · 495 across the 11 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2023★ 24 cited

Exploring Large Language Models for Knowledge Graph Completion

Liang Yao, Jiazhen Peng, Chengsheng Mao +1

Knowledge graphs play a vital role in numerous artificial intelligence tasks, yet they frequently face the issue of incompleteness. In this study, we explore utilizing Large Langua…

cs.CL2019★ 382 cited

KG-BERT: BERT for Knowledge Graph Completion

Liang Yao, Chengsheng Mao, Yuan Luo

Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness. In this work, we propose to use pre-trained language models fo…

cs.CL2019★ 12 cited

Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study

Prakash Adekkanattu, Guoqian Jiang, Yuan Luo +14

While natural language processing (NLP) of unstructured clinical narratives holds the potential for patient care and clinical research, portability of NLP approaches across multipl…

cs.CL2018★ 61 cited

Graph Convolutional Networks for Text Classification

Liang Yao, Chengsheng Mao, Yuan Luo

Text classification is an important and classical problem in natural language processing. There have been a number of studies that applied convolutional neural networks (convolutio…

cs.CL2018

Clinical Text Classification with Rule-based Features and Knowledge-guided Convolutional Neural Networks

Liang Yao, Chengsheng Mao, Yuan Luo

Clinical text classification is an important problem in medical natural language processing. Existing studies have conventionally focused on rules or knowledge sources-based featur…

cs.CL2018

Developing a Portable Natural Language Processing Based Phenotyping System

Himanshu Sharma, Chengsheng Mao, Yizhen Zhang +7

This paper presents a portable phenotyping system that is capable of integrating both rule-based and statistical machine learning based approaches. Our system utilizes UMLS to extr…