{"title":"走向高效的医疗搜索引擎","authors":"M. A. Zamil, Aysu Betin Can","doi":"10.1109/HIBIT.2010.5478911","DOIUrl":null,"url":null,"abstract":"In this paper, we present a domain specific search engine that relies on extracting the semantic relation among medical documents. Our goal is to maximize the contextual retrieval and ranking performance with minimum input from users. We have performed experiments to measure the effectiveness of the proposed technique by evaluating the performance of the retrieval process in terms of recall, precision and topical ranking. The results indicated that the proposed medical search engine achieved higher average precision in compare with highest scored runs submitted to TREC-9.","PeriodicalId":215457,"journal":{"name":"2010 5th International Symposium on Health Informatics and Bioinformatics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Toward effective medical search engines\",\"authors\":\"M. A. Zamil, Aysu Betin Can\",\"doi\":\"10.1109/HIBIT.2010.5478911\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a domain specific search engine that relies on extracting the semantic relation among medical documents. Our goal is to maximize the contextual retrieval and ranking performance with minimum input from users. We have performed experiments to measure the effectiveness of the proposed technique by evaluating the performance of the retrieval process in terms of recall, precision and topical ranking. The results indicated that the proposed medical search engine achieved higher average precision in compare with highest scored runs submitted to TREC-9.\",\"PeriodicalId\":215457,\"journal\":{\"name\":\"2010 5th International Symposium on Health Informatics and Bioinformatics\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 5th International Symposium on Health Informatics and Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIBIT.2010.5478911\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 5th International Symposium on Health Informatics and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIBIT.2010.5478911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we present a domain specific search engine that relies on extracting the semantic relation among medical documents. Our goal is to maximize the contextual retrieval and ranking performance with minimum input from users. We have performed experiments to measure the effectiveness of the proposed technique by evaluating the performance of the retrieval process in terms of recall, precision and topical ranking. The results indicated that the proposed medical search engine achieved higher average precision in compare with highest scored runs submitted to TREC-9.