{"title":"一种基于高相关性关键词的深度网络数据库采样方法","authors":"Yongqing Zheng, Yufang Bian, Xin Du, Hongchen Wu","doi":"10.1109/WISA.2012.25","DOIUrl":null,"url":null,"abstract":"Evaluation of the Deep Web data sources must be based on the data in the Web databases, then how to select the most representative keywords as a query word to obtain a large number of uniformly distributed data is a major difficulty, this paper proposed a Deep Web database sampling method based on high correlation keyword, using a graph based keyword-connected network to get query words, the method can get a random sample of high-quality data from the Deep Web data source more efficiently.","PeriodicalId":313228,"journal":{"name":"2012 Ninth Web Information Systems and Applications Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Deep Web Database Sampling Method Based on High Correlation Keywords\",\"authors\":\"Yongqing Zheng, Yufang Bian, Xin Du, Hongchen Wu\",\"doi\":\"10.1109/WISA.2012.25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evaluation of the Deep Web data sources must be based on the data in the Web databases, then how to select the most representative keywords as a query word to obtain a large number of uniformly distributed data is a major difficulty, this paper proposed a Deep Web database sampling method based on high correlation keyword, using a graph based keyword-connected network to get query words, the method can get a random sample of high-quality data from the Deep Web data source more efficiently.\",\"PeriodicalId\":313228,\"journal\":{\"name\":\"2012 Ninth Web Information Systems and Applications Conference\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Ninth Web Information Systems and Applications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WISA.2012.25\",\"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 Ninth Web Information Systems and Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISA.2012.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Deep Web Database Sampling Method Based on High Correlation Keywords
Evaluation of the Deep Web data sources must be based on the data in the Web databases, then how to select the most representative keywords as a query word to obtain a large number of uniformly distributed data is a major difficulty, this paper proposed a Deep Web database sampling method based on high correlation keyword, using a graph based keyword-connected network to get query words, the method can get a random sample of high-quality data from the Deep Web data source more efficiently.
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