Tianyong Hao


2018

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T-Know: a Knowledge Graph-based Question Answering and Infor-mation Retrieval System for Traditional Chinese Medicine
Ziqing Liu | Enwei Peng | Shixing Yan | Guozheng Li | Tianyong Hao
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations

T-Know is a knowledge service system based on the constructed knowledge graph of Traditional Chinese Medicine (TCM). Using authorized and anonymized clinical records, medicine clinical guidelines, teaching materials, classic medical books, academic publications, etc., as data resources, the system extracts triples from free texts to build a TCM knowledge graph by our developed natural language processing methods. On the basis of the knowledge graph, a deep learning algorithm is implemented for single-round question understanding and multiple-round dialogue. In addition, the TCM knowledge graph also is used to support human-computer interactive knowledge retrieval by normalizing search keywords to medical terminology.

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Annotating Measurable Quantitative Informationin Language: for an ISO Standard
Tianyong Hao | Haotai Wang | Xinyu Cao | Kiyong Lee
Proceedings 14th Joint ACL - ISO Workshop on Interoperable Semantic Annotation

2017

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The representation and extraction of qunatitative information
Tianyong Hao | Yunyan We | Jiaqi Qiang | Haitao Wang | Kiyong Lee
Proceedings of the 13th Joint ISO-ACL Workshop on Interoperable Semantic Annotation (ISA-13)

2010

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Towards Automatic Question Answering over Social Media by Learning Question Equivalence Patterns
Tianyong Hao | Wenyin Liu | Eugene Agichtein
Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a World of Social Media