A. Bampoulidis, M. Lupu, João Palotti, S. Metallidis, J. Brassey, A. Hanbury
{"title":"医疗保健查询的交互式探索","authors":"A. Bampoulidis, M. Lupu, João Palotti, S. Metallidis, J. Brassey, A. Hanbury","doi":"10.1109/CBMI.2016.7500275","DOIUrl":null,"url":null,"abstract":"Healthcare related queries are a treasure trove of information about the information needs of domain users, be they patients or doctors. However, unlike general queries, in order to make the most out of the information therein, such queries have to be processed within a medical terminology annotation pipeline. We show how this has been done in the context of the KConnect project and demonstrate an interactive query log exploration interface that allows data analysts and search engineers to better understand their users and design a better search experience.","PeriodicalId":356608,"journal":{"name":"2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Interactive exploration of healthcare queries\",\"authors\":\"A. Bampoulidis, M. Lupu, João Palotti, S. Metallidis, J. Brassey, A. Hanbury\",\"doi\":\"10.1109/CBMI.2016.7500275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Healthcare related queries are a treasure trove of information about the information needs of domain users, be they patients or doctors. However, unlike general queries, in order to make the most out of the information therein, such queries have to be processed within a medical terminology annotation pipeline. We show how this has been done in the context of the KConnect project and demonstrate an interactive query log exploration interface that allows data analysts and search engineers to better understand their users and design a better search experience.\",\"PeriodicalId\":356608,\"journal\":{\"name\":\"2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMI.2016.7500275\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMI.2016.7500275","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Healthcare related queries are a treasure trove of information about the information needs of domain users, be they patients or doctors. However, unlike general queries, in order to make the most out of the information therein, such queries have to be processed within a medical terminology annotation pipeline. We show how this has been done in the context of the KConnect project and demonstrate an interactive query log exploration interface that allows data analysts and search engineers to better understand their users and design a better search experience.
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