Chronic disease related entity extraction in online Chinese question and answer services

Yan Zhang, Yong Zhang, Yanshen Yin, Jennifer Xu, Chunxiao Xing, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Chinese chronic disease entity extraction aims to extract health related entities from online questions and answers (QA). Our research tackles challenges in Chinese chronic disease entity extraction from three aspects: Chinese health lexicons construction, feature development, and equivalence conjunctions tagging. We construct large scale Chinese health lexicons based on expert knowledge and the Web resources; develop a feature extraction approach that draws out character, part-of-speech, and lexical features from QA data; and improve the performance of answer entity extraction by leveraging equivalence conjunctions (punctuation marks and conjunctional words) in Chinese to capture dependencies between tags of entities. Experiments on question and answer entity extraction demonstrate that the Precision, Recall and F-1 score are improved using our proposed features, and the Precision and F-1 score can be further improved by considering equivalence conjunctions.

Original languageEnglish (US)
Title of host publicationSmart Health - International Conference, ICSH 2015, Revised Selected Papers
EditorsHsinchun Chen, Daniel Dajun Zeng, Xiaolong Zheng, Scott J. Leischow
Number of pages13
ISBN (Print)9783319291741
StatePublished - 2016
EventInternational Conference for Smart Health, ICSH 2015 - Phoenix, United States
Duration: Nov 17 2015Nov 18 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherInternational Conference for Smart Health, ICSH 2015
Country/TerritoryUnited States


  • Entity extraction
  • Health lexicon
  • QA

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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