| ²é¿´: 942 | »Ø¸´: 2 | |||
tracy7777777гæ (³õÈëÎÄ̳)
|
[ÇóÖú]
Çó°ï¿´¿´ÓÐûÓÐÔÚsci¼ìË÷µ½ Èë²ØºÅÓÐÂð ÒÑÓÐ1È˲ÎÓë
|
|
title£º context-sensitive spelling correction of consumer-generated context on health care JMIR Med inform 2015 3¾í 3ÆÚ µç×Ó°æ²éµÄµ½£¬×¼±¸È¥´ò¼ìË÷Ö¤Ã÷£¬²»ÖªµÀÓÐûÓб»sciÊÕ¼£¬ÇëÄÄλ´óÉñ°ïæ¿´¿´£¬Ð»Ð»£¡£¡£¡ |
» ²ÂÄãϲ»¶
ÎÒÃæÉÏÍêµ°ÁË
ÒѾÓÐ11È˻ظ´
ÊÛSCIÒ»ÇøÎÄÕ£¬ÎÒ:8.O.551.O.5.4,¿ÆÄ¿È«,¿ÉÙ¤¼±
ÒѾÓÐ8È˻ظ´
ÊÛSCIÒ»ÇøÎÄÕ£¬ÎÒ:8.O.55.1.O.54,¿ÆÄ¿ÆëÈ«,¿ÉÙ¤¼±
ÒѾÓÐ3È˻ظ´
Ã÷ÌìÓ¦¸Ã¿É²éÁË£¡£¿
ÒѾÓÐ5È˻ظ´
Èç¹û´Ë¿ÌÄãÕýÔÚΪ¹ú»ù¸Ðµ½½¹ÂÇ£¬²»·ÁÀ´ÌýÌýÕâÊס¶»ù½ðÖ®Íâ¡·
ÒѾÓÐ7È˻ظ´
ûÓÐÈκÎÏûÏ¢-ÊDz»ÊǾÍÁ¹ÁË
ÒѾÓÐ8È˻ظ´
ÊÛSCI-T0PÎÄÕ£¬ÎÒ:8O.5.5.1.O.54,¿ÆÄ¿ÆëÈ«,¿É+¼±
ÒѾÓÐ3È˻ظ´
ÈËÆø²»ÐÐÁË
ÒѾÓÐ10È˻ظ´
ÄÜ·ñÍ˳ö²ÎÓëµÄÃæÉÏÏîÄ¿½â³ýÏÞÏî
ÒѾÓÐ24È˻ظ´
filecode£¬4¸öjtjcÁË
ÒѾÓÐ17È˻ظ´
liouzhan654
°æÖ÷ (ÖªÃû×÷¼Ò)
- Ó¦Öú: 798 (²©ºó)
- ¹ó±ö: 5.504
- ½ð±Ò: 53654.6
- É¢½ð: 5660
- ºì»¨: 182
- ɳ·¢: 8
- Ìû×Ó: 9431
- ÔÚÏß: 2139.6Сʱ
- ³æºÅ: 2048939
- ×¢²á: 2012-10-08
- ÐÔ±ð: GG
- רҵ: ´«ÈÈ´«ÖÊѧ
- ¹ÜϽ: ÂÛÎÄͶ¸å
¡¾´ð°¸¡¿Ó¦Öú»ØÌû
¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï
¸Ðл²ÎÓ룬ӦÖúÖ¸Êý +1
tracy7777777: ½ð±Ò+10, ¡ï¡ï¡ï¡ï¡ï×î¼Ñ´ð°¸, ̫ллÁË 2016-12-22 19:33:34
paperhunter: ½ð±Ò+2, ¹ÄÀø½»Á÷ 2016-12-22 21:40:35
¸Ðл²ÎÓ룬ӦÖúÖ¸Êý +1
tracy7777777: ½ð±Ò+10, ¡ï¡ï¡ï¡ï¡ï×î¼Ñ´ð°¸, ̫ллÁË 2016-12-22 19:33:34
paperhunter: ½ð±Ò+2, ¹ÄÀø½»Á÷ 2016-12-22 21:40:35
|
Context-Sensitive Spelling Correction of Consumer-Generated Content on Health Care ×÷Õß: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 ] ²é¿´ ResearcherID ºÍ ORCID JMIR MEDICAL INFORMATICS ¾í: 3 ÆÚ: 3 Ò³: 2-11 ÎÄÏ׺Å: e27 DOI: 10.2196/medinform.4211 ³ö°æÄê: JUL-SEP 2015 ÕªÒª 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. ¹Ø¼ü´Ê ×÷Õ߹ؼü´Ê:spelling correction system; context sensitive; consumer-generated content; biomedical ontology KeyWords Plus:MEDICATION EXTRACTION; DISAMBIGUATION; INFORMATION; PATIENT; ERRORS ×÷ÕßÐÅÏ¢ ͨѶ×÷ÕßµØÖ·: Xia, T (ͨѶ×÷Õß) ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Internet Technol & Engn Res & Dev Ctr, 1037 Luoyu Rd, Nanyi 430074, Peoples R China. µØÖ·: [ 1 ] Wuhan Cent Hosp, Dept Ophthalmol, Wuhan, Peoples R China ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ [ 2 ] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Internet Technol & Engn Res & Dev Ctr, Wuhan 430074, Peoples R China ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ [ 3 ] Fudan Univ, Sch Life Sci, Dept Biostat & Computat Biol, Shanghai 200433, Peoples R China ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ [ 4 ] Northwestern Univ, Feinberg Sch Med, NUBIC, Chicago, IL 60611 USA ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ [ 5 ] Nationwide Childrens Hosp, Res Inst, Columbus, OH USA µç×ÓÓʼþµØÖ·:tianxia@hust.edu.cn ³ö°æÉÌ JMIR PUBLICATIONS, INC, 59 WINNERS CIRCLE, TORONTO, ON M4L 3Y7, CANADA Àà±ð / ·ÖÀà Ñо¿·½Ïò:Medical Informatics Web of Science Àà±ð:Medical Informatics ÎÄÏ×ÐÅÏ¢ ÎÄÏ×ÀàÐÍ:Article ÓïÖÖ:English Èë²ØºÅ: WOS:000359790200001 PubMed ID: 26232246 ISSN: 2291-9694 ÆäËûÐÅÏ¢ IDS ºÅ: CP3OR Web of Science ºËÐĺϼ¯ÖÐµÄ "ÒýÓõIJο¼ÎÄÏ×": 20 Web of Science ºËÐĺϼ¯ÖÐµÄ "±»ÒýƵ´Î": 0 |

2Â¥2016-12-22 08:47:28
tracy7777777
гæ (³õÈëÎÄ̳)
- Ó¦Öú: 0 (Ó×¶ùÔ°)
- ½ð±Ò: 13
- Ìû×Ó: 5
- ÔÚÏß: 1Сʱ
- ³æºÅ: 4126116
- ×¢²á: 2015-10-08
- רҵ: ÑÛ¿ÆÑ§
3Â¥2016-12-22 19:33:10









»Ø¸´´ËÂ¥