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title：
context-sensitive spelling correction of consumer-generated context on health care
JMIR Med inform 2015 3卷 3期
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Context-Sensitive Spelling Correction of Consumer-Generated Content on Health Care
作者:Zhou, XF (Zhou, Xiaofang)[ 1,2 ] ; Zheng, A (Zheng, An)[ 2 ] ; Yin, JH (Yin, Jiaheng)[ 2,3 ] ; Chen, RD (Chen, Rudan)[ 2 ] ; Zhao, XY (Zhao, Xianyang)[ 2 ] ; Xu, W (Xu, Wei)[ 2 ] ; Cheng, WQ (Cheng, Wenqing)[ 2 ] ; Xia, T (Xia, Tian)[ 2,4 ] ; Lin, S (Lin, Simon)[ 5 ]
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JMIR MEDICAL INFORMATICS
卷: 3 期: 3 页: 2-11
文献号: e27
DOI: 10.2196/medinform.4211
出版年: JUL-SEP 2015
摘要
Background: Consumer-generated content, such as postings on social media websites, can serve as an ideal source of information for studying health care from a consumer's perspective. However, consumer-generated content on health care topics often contains spelling errors, which, if not corrected, will be obstacles for downstream computer-based text analysis.

Objective: In this study, we proposed a framework with a spelling correction system designed for consumer-generated content and a novel ontology-based evaluation system which was used to efficiently assess the correction quality. Additionally, we emphasized the importance of context sensitivity in the correction process, and demonstrated why correction methods designed for electronic medical records (EMRs) failed to perform well with consumer-generated content.

Methods: First, we developed our spelling correction system based on Google Spell Checker. The system processed postings acquired from MedHelp, a biomedical bulletin board system (BBS), and saved misspelled words (eg, sertaline) and corresponding corrected words (eg, sertraline) into two separate sets. Second, to reduce the number of words needing manual examination in the evaluation process, we respectively matched the words in the two sets with terms in two biomedical ontologies: RxNorm and Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). The ratio of words which could be matched and appropriately corrected was used to evaluate the correction system's overall performance. Third, we categorized the misspelled words according to the types of spelling errors. Finally, we calculated the ratio of abbreviations in the postings, which remarkably differed between EMRs and consumer-generated content and could largely influence the overall performance of spelling checkers.

Results: An uncorrected word and the corresponding corrected word was called a spelling pair, and the two words in the spelling pair were its members. In our study, there were 271 spelling pairs detected, among which 58 (21.4%) pairs had one or two members matched in the selected ontologies. The ratio of appropriate correction in the 271 overall spelling errors was 85.2% (231/271). The ratio of that in the 58 spelling pairs was 86% (50/58), close to the overall ratio. We also found that linguistic errors took up 31.4% (85/271) of all errors detected, and only 0.98% (210/21,358) of words in the postings were abbreviations, which was much lower than the ratio in the EMRs (33.6%).

Conclusions: We conclude that our system can accurately correct spelling errors in consumer-generated content. Context sensitivity is indispensable in the correction process. Additionally, it can be confirmed that consumer-generated content differs from EMRs in that consumers seldom use abbreviations. Also, the evaluation method, taking advantage of biomedical ontology, can effectively estimate the accuracy of the correction system and reduce manual examination time.
关键词
作者关键词:spelling correction system; context sensitive; consumer-generated content; biomedical ontology
KeyWords Plus:MEDICATION EXTRACTION; DISAMBIGUATION; INFORMATION; PATIENT; ERRORS
作者信息
通讯作者地址: Xia, T (通讯作者)
显示增强组织信息的名称 Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Internet Technol & Engn Res & Dev Ctr, 1037 Luoyu Rd, Nanyi 430074, Peoples R China.
地址:
[ 1 ] Wuhan Cent Hosp, Dept Ophthalmol, Wuhan, Peoples R China
显示增强组织信息的名称 [ 2 ] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Internet Technol & Engn Res & Dev Ctr, Wuhan 430074, Peoples R China
显示增强组织信息的名称 [ 3 ] Fudan Univ, Sch Life Sci, Dept Biostat & Computat Biol, Shanghai 200433, Peoples R China
显示增强组织信息的名称 [ 4 ] Northwestern Univ, Feinberg Sch Med, NUBIC, Chicago, IL 60611 USA
显示增强组织信息的名称 [ 5 ] Nationwide Childrens Hosp, Res Inst, Columbus, OH USA
电子邮件地址:tianxia@hust.edu.cn
出版商
JMIR PUBLICATIONS, INC, 59 WINNERS CIRCLE, TORONTO, ON M4L 3Y7, CANADA
类别 / 分类
研究方向:Medical Informatics
Web of Science 类别:Medical Informatics
文献信息
文献类型:Article
语种:English
入藏号: WOS:000359790200001
PubMed ID: 26232246
ISSN: 2291-9694
其他信息
IDS 号: CP3OR
Web of Science 核心合集中的 "引用的参考文献": 20
Web of Science 核心合集中的 "被引频次": 0