{"title":"多媒体数据质量建模的实用方法","authors":"Kwan-Sang Na, D. Baik, Pan-koo Kim","doi":"10.1145/500141.500228","DOIUrl":null,"url":null,"abstract":"One of the most important objectives of data engineering is to deliver high quality data to users. In this paper, we (1) discuss the definition, problems and improvements methods of data qwuality, and (2) propose a modeling methodology for improving the multimedia data quality. And then, we introduce the method for improving the quality of semantic data using the proposed methodology. In this example, we propose to measure and remove the data ambiguities for improving the data quality.","PeriodicalId":416848,"journal":{"name":"MULTIMEDIA '01","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A practical approach for modeling the quality of multimedia data\",\"authors\":\"Kwan-Sang Na, D. Baik, Pan-koo Kim\",\"doi\":\"10.1145/500141.500228\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the most important objectives of data engineering is to deliver high quality data to users. In this paper, we (1) discuss the definition, problems and improvements methods of data qwuality, and (2) propose a modeling methodology for improving the multimedia data quality. And then, we introduce the method for improving the quality of semantic data using the proposed methodology. In this example, we propose to measure and remove the data ambiguities for improving the data quality.\",\"PeriodicalId\":416848,\"journal\":{\"name\":\"MULTIMEDIA '01\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MULTIMEDIA '01\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/500141.500228\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MULTIMEDIA '01","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/500141.500228","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A practical approach for modeling the quality of multimedia data
One of the most important objectives of data engineering is to deliver high quality data to users. In this paper, we (1) discuss the definition, problems and improvements methods of data qwuality, and (2) propose a modeling methodology for improving the multimedia data quality. And then, we introduce the method for improving the quality of semantic data using the proposed methodology. In this example, we propose to measure and remove the data ambiguities for improving the data quality.