{"title":"参见你所知道的:分析数据分布以改善密度图的可视化","authors":"E. Bertini, A. D. Girolamo, G. Santucci","doi":"10.2312/VisSym/EuroVis07/163-170","DOIUrl":null,"url":null,"abstract":"Density maps allow for visually rendering density differences, usually mapping density values to a grey or color scale. The paper analyzes the drawbacks arising from the commonly used strategies and introduces a novel technique able to improve the overall mapping process. The technique is driven by statistical knowledge about the density distribution and a set of quality metrics allows for validating, in an objective way, its effectiveness.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"See What You Know: Analyzing Data Distribution to Improve Density Map Visualization\",\"authors\":\"E. Bertini, A. D. Girolamo, G. Santucci\",\"doi\":\"10.2312/VisSym/EuroVis07/163-170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Density maps allow for visually rendering density differences, usually mapping density values to a grey or color scale. The paper analyzes the drawbacks arising from the commonly used strategies and introduces a novel technique able to improve the overall mapping process. The technique is driven by statistical knowledge about the density distribution and a set of quality metrics allows for validating, in an objective way, its effectiveness.\",\"PeriodicalId\":224719,\"journal\":{\"name\":\"Eurographics Conference on Visualization\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eurographics Conference on Visualization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2312/VisSym/EuroVis07/163-170\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eurographics Conference on Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/VisSym/EuroVis07/163-170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
See What You Know: Analyzing Data Distribution to Improve Density Map Visualization
Density maps allow for visually rendering density differences, usually mapping density values to a grey or color scale. The paper analyzes the drawbacks arising from the commonly used strategies and introduces a novel technique able to improve the overall mapping process. The technique is driven by statistical knowledge about the density distribution and a set of quality metrics allows for validating, in an objective way, its effectiveness.