{"title":"一个图形,多个绘图","authors":"M. Nadal, G. Melanon","doi":"10.1109/IV.2013.55","DOIUrl":null,"url":null,"abstract":"Being able to produce a wide variety of layouts for a same graphs may prove useful when users have no preferred visual encoding for their data. The first contribution of this paper is a enhanced force-directed layout capable of producing different layouts of a same graph. We turn a well known force-directed algorithm (GEM) into a highly parametrizable layout and control it from a genetic algorithm framework. The genetic algorithm allows to efficiently explore the parameter space of this highly parametrisable layout. The search process relies on the capability of the system to evaluate the similarity between two drawings. The second contribution of this paper is a similarity metric used as a fitness function for the genetic algorithm. Its main features are its computational cost and its insensitivity to planar homotheties.","PeriodicalId":354135,"journal":{"name":"2013 17th International Conference on Information Visualisation","volume":"222 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"One Graph, Multiple Drawings\",\"authors\":\"M. Nadal, G. Melanon\",\"doi\":\"10.1109/IV.2013.55\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Being able to produce a wide variety of layouts for a same graphs may prove useful when users have no preferred visual encoding for their data. The first contribution of this paper is a enhanced force-directed layout capable of producing different layouts of a same graph. We turn a well known force-directed algorithm (GEM) into a highly parametrizable layout and control it from a genetic algorithm framework. The genetic algorithm allows to efficiently explore the parameter space of this highly parametrisable layout. The search process relies on the capability of the system to evaluate the similarity between two drawings. The second contribution of this paper is a similarity metric used as a fitness function for the genetic algorithm. Its main features are its computational cost and its insensitivity to planar homotheties.\",\"PeriodicalId\":354135,\"journal\":{\"name\":\"2013 17th International Conference on Information Visualisation\",\"volume\":\"222 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 17th International Conference on Information Visualisation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IV.2013.55\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 17th International Conference on Information Visualisation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IV.2013.55","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Being able to produce a wide variety of layouts for a same graphs may prove useful when users have no preferred visual encoding for their data. The first contribution of this paper is a enhanced force-directed layout capable of producing different layouts of a same graph. We turn a well known force-directed algorithm (GEM) into a highly parametrizable layout and control it from a genetic algorithm framework. The genetic algorithm allows to efficiently explore the parameter space of this highly parametrisable layout. The search process relies on the capability of the system to evaluate the similarity between two drawings. The second contribution of this paper is a similarity metric used as a fitness function for the genetic algorithm. Its main features are its computational cost and its insensitivity to planar homotheties.