{"title":"Twitter上个人健康信息的文本挖掘","authors":"Marina Sokolova, Yasser Jafer, D. Schramm","doi":"10.1109/HISB.2012.37","DOIUrl":null,"url":null,"abstract":"With millions people discussing their Personal Health Information (PHI) online, there is a need for the development of tools that can extract and analyze such information. We introduce two semantic-based methods for mining PHI. One method uses WordNet as a source of health-related knowledge, another - terms of personal relations. Incorporating semantics gives a significant improvement in retrieval of text with PHI (paired t-test, P = 0.0001).","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"300 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Text Mining for Personal Health Information on Twitter\",\"authors\":\"Marina Sokolova, Yasser Jafer, D. Schramm\",\"doi\":\"10.1109/HISB.2012.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With millions people discussing their Personal Health Information (PHI) online, there is a need for the development of tools that can extract and analyze such information. We introduce two semantic-based methods for mining PHI. One method uses WordNet as a source of health-related knowledge, another - terms of personal relations. Incorporating semantics gives a significant improvement in retrieval of text with PHI (paired t-test, P = 0.0001).\",\"PeriodicalId\":375089,\"journal\":{\"name\":\"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology\",\"volume\":\"300 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HISB.2012.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HISB.2012.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Text Mining for Personal Health Information on Twitter
With millions people discussing their Personal Health Information (PHI) online, there is a need for the development of tools that can extract and analyze such information. We introduce two semantic-based methods for mining PHI. One method uses WordNet as a source of health-related knowledge, another - terms of personal relations. Incorporating semantics gives a significant improvement in retrieval of text with PHI (paired t-test, P = 0.0001).