| 查看: 953 | 回复: 2 | |||
[求助]
求帮看看有没有在sci检索到 入藏号有吗 已有1人参与
|
|
title： context-sensitive spelling correction of consumer-generated context on health care JMIR Med inform 2015 3卷 3期 电子版查的到，准备去打检索证明，不知道有没有被sci收录，请哪位大神帮忙看看，谢谢！！！ |
回复此楼» 猜你喜欢
售SCI一区文章，我:8.O.551.O.5.4,科目全,可伽急
已经有6人回复
-
售SCI文章，我:8O.5.5.1O.54,科目全,可十急
已经有8人回复
-
售SCI文章，我:8O.5.5.1O.54,科目全,可十急
已经有5人回复
-
售SCI一区T0P文章，我:8O.55.1.O.5.4,科目齐全,可+急
已经有10人回复
-
售一区SCI文章T0P，我:8O.551.O54,科目全,可十急
已经有6人回复
-
售SCI一区T0P文章，我:8O.55.1.O.54,科目全,可伽急
已经有9人回复
-
售SCI一区T0P文章，我:8.O55.1.O.54,科目全,可十急
已经有8人回复
-
国社科又开始会评了，不知道这次命运如何
已经有14人回复
-
售SCI一区文章，我:8.O.55.1.O.54,科目齐全,可伽急
已经有8人回复
-
麻烦专家们看看评委们的意见（F口面上）
已经有13人回复
liouzhan654
版主 (知名作家)
- 应助: 798 (博后)
- 贵宾: 5.504
- 金币: 53654.6
- 散金: 5660
- 红花: 182
- 沙发: 8
- 帖子: 9431
- 在线: 2139.6小时
- 虫号: 2048939
- 注册: 2012-10-08
- 性别: GG
- 专业: 传热传质学
- 管辖: 论文投稿
【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
tracy7777777: 金币+10, ★★★★★最佳答案, 太谢谢了 2016-12-22 19:33:34
paperhunter: 金币+2, 鼓励交流 2016-12-22 21:40:35
感谢参与，应助指数 +1
tracy7777777: 金币+10, ★★★★★最佳答案, 太谢谢了 2016-12-22 19:33:34
paperhunter: 金币+2, 鼓励交流 2016-12-22 21:40:35
|
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 ] 查看 ResearcherID 和 ORCID 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 |
2楼2016-12-22 08:47:28
3楼2016-12-22 19:33:10
30