{"title":"在Medline文档中查找主题-概率相似性搜索","authors":"H. Shatkey, W. Wilber","doi":"10.1109/ADL.2000.848381","DOIUrl":null,"url":null,"abstract":"Large on-line document databases, such as Medine, pose a major challenge of retrieving the few documents most relevant to the user's needs, while multimizing the return rate of nonrelevant documents. Retrieval of documents similar to a user provided example document is a promising query paradigm towards meeting this goal. We present a new theme-based probabilistic approach for finding documents relevant to a given query document, and summarizing their contents. Preliminary experiments conducted over a subset of Medline documents related to AIDS demonstrate the effectiveness of our approach.","PeriodicalId":426762,"journal":{"name":"Proceedings IEEE Advances in Digital Libraries 2000","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Finding themes in Medline documents - probabilistic similarity search\",\"authors\":\"H. Shatkey, W. Wilber\",\"doi\":\"10.1109/ADL.2000.848381\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Large on-line document databases, such as Medine, pose a major challenge of retrieving the few documents most relevant to the user's needs, while multimizing the return rate of nonrelevant documents. Retrieval of documents similar to a user provided example document is a promising query paradigm towards meeting this goal. We present a new theme-based probabilistic approach for finding documents relevant to a given query document, and summarizing their contents. Preliminary experiments conducted over a subset of Medline documents related to AIDS demonstrate the effectiveness of our approach.\",\"PeriodicalId\":426762,\"journal\":{\"name\":\"Proceedings IEEE Advances in Digital Libraries 2000\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE Advances in Digital Libraries 2000\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ADL.2000.848381\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings IEEE Advances in Digital Libraries 2000","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ADL.2000.848381","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finding themes in Medline documents - probabilistic similarity search
Large on-line document databases, such as Medine, pose a major challenge of retrieving the few documents most relevant to the user's needs, while multimizing the return rate of nonrelevant documents. Retrieval of documents similar to a user provided example document is a promising query paradigm towards meeting this goal. We present a new theme-based probabilistic approach for finding documents relevant to a given query document, and summarizing their contents. Preliminary experiments conducted over a subset of Medline documents related to AIDS demonstrate the effectiveness of our approach.