{"title":"在异构环境中实现高效的多特征查询","authors":"Ulrich Güntzer, Wolf-Tilo Balke, Werner Kießling","doi":"10.1109/ITCC.2001.918866","DOIUrl":null,"url":null,"abstract":"Applications like multimedia databases or enterprise-wide information management systems have to meet the challenge of efficiently retrieving the best-matching objects from vast collections of data. We present a new algorithm, called Stream-Combine, for processing multi-feature queries on heterogeneous data sources. Stream-Combine is self-adapting to different data distributions and to the specific kind of the combining function. Furthermore, we present a new retrieval strategy that essentially speeds up the output of relevant objects.","PeriodicalId":318295,"journal":{"name":"Proceedings International Conference on Information Technology: Coding and Computing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"138","resultStr":"{\"title\":\"Towards efficient multi-feature queries in heterogeneous environments\",\"authors\":\"Ulrich Güntzer, Wolf-Tilo Balke, Werner Kießling\",\"doi\":\"10.1109/ITCC.2001.918866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Applications like multimedia databases or enterprise-wide information management systems have to meet the challenge of efficiently retrieving the best-matching objects from vast collections of data. We present a new algorithm, called Stream-Combine, for processing multi-feature queries on heterogeneous data sources. Stream-Combine is self-adapting to different data distributions and to the specific kind of the combining function. Furthermore, we present a new retrieval strategy that essentially speeds up the output of relevant objects.\",\"PeriodicalId\":318295,\"journal\":{\"name\":\"Proceedings International Conference on Information Technology: Coding and Computing\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"138\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings International Conference on Information Technology: Coding and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITCC.2001.918866\",\"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 International Conference on Information Technology: Coding and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCC.2001.918866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards efficient multi-feature queries in heterogeneous environments
Applications like multimedia databases or enterprise-wide information management systems have to meet the challenge of efficiently retrieving the best-matching objects from vast collections of data. We present a new algorithm, called Stream-Combine, for processing multi-feature queries on heterogeneous data sources. Stream-Combine is self-adapting to different data distributions and to the specific kind of the combining function. Furthermore, we present a new retrieval strategy that essentially speeds up the output of relevant objects.