@inproceedings{be053105eec944de8eafe9a7f8a650cb,
title = "UTH\_CCB: A Report for SemEval 2014 – Task 7 Analysis of Clinical Text",
abstract = "This work describes the participation of the University of Texas Health Science Center at Houston (UTHealth) team on the SemEval 2014 – Task 7 analysis of clinical text challenge. The task consisted of two subtasks: (1) disorder entity recognition, recognizing mentions of disorder concepts; (2) disorder entity encoding, mapping each mention to a unique Concept Unique Identifier (CUI) defined in Unified Medical Language System (UMLS). We developed three ensemble learning approaches for recognizing disorder entities and a Vector Space Model based method for encoding. Our approaches achieved top rank in both subtasks, with the best F measure of 0.813 for entity recognition and the best accuracy of 74.1\% for encoding, indicating the proposed approaches are promising.",
author = "Yaoyun Zhang and Jingqi Wang and Buzhou Tang and Yonghui Wu and Min Jiang and Yukun Chen and Hua Xu",
note = "Publisher Copyright: {\textcopyright} 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings. All rights reserved.; 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014 ; Conference date: 23-08-2014 Through 24-08-2014",
year = "2014",
doi = "10.3115/v1/s14-2142",
language = "英语",
series = "8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "802--806",
editor = "Preslav Nakov and Torsten Zesch",
booktitle = "8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings",
address = "澳大利亚",
}