{"title":"Building a visual database for example-based graphics generation","authors":"Michelle X. Zhou, Min Chen, Ying Feng","doi":"10.1109/INFVIS.2002.1173143","DOIUrl":null,"url":null,"abstract":"Example-based graphics generation systems automatically create new information visualizations by learning from existing graphic examples. As part of the effort on developing a general-purpose example-based generation system, we are building a visual database of graphic examples. In this paper, we address two main issues involved in constructing such a database: example selection and example modeling. As a result, our work offers three unique contributions: First, we build a visual database that contains a diverse collection of well-designed examples. Second, we develop a feature-based scheme to model all examples uniformly and accurately. Third, our visual database brings several important implications to the area of information visualization.","PeriodicalId":293232,"journal":{"name":"IEEE Symposium on Information Visualization, 2002. INFOVIS 2002.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Symposium on Information Visualization, 2002. INFOVIS 2002.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFVIS.2002.1173143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
Example-based graphics generation systems automatically create new information visualizations by learning from existing graphic examples. As part of the effort on developing a general-purpose example-based generation system, we are building a visual database of graphic examples. In this paper, we address two main issues involved in constructing such a database: example selection and example modeling. As a result, our work offers three unique contributions: First, we build a visual database that contains a diverse collection of well-designed examples. Second, we develop a feature-based scheme to model all examples uniformly and accurately. Third, our visual database brings several important implications to the area of information visualization.