Edward Clarkson, J. Choo, John Turgeson, R. Decuir, Haesun Park
{"title":"分析:综合高维算法分析与领域不可知论,面可视化分析","authors":"Edward Clarkson, J. Choo, John Turgeson, R. Decuir, Haesun Park","doi":"10.1145/2501511.2501518","DOIUrl":null,"url":null,"abstract":"We present Lytic, a domain-independent, faceted visual analytic (VA) system for interactive exploration of large datasets. It combines a flexible UI that adapts to arbitrary character-separated value (CSV) datasets with algorithmic preprocessing to compute unsupervised dimension reduction and cluster data from high-dimensional fields. It provides a variety of visualization options that require minimal user effort to configure and a consistent user experience between visualization types and underlying datasets. Filtering, comparison and visualization operations work in concert, allowing users to hop seamlessly between actions and pursue answers to expected and unexpected data hypotheses.","PeriodicalId":126062,"journal":{"name":"Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Lytic: synthesizing high-dimensional algorithmic analysis with domain-agnostic, faceted visual analytics\",\"authors\":\"Edward Clarkson, J. Choo, John Turgeson, R. Decuir, Haesun Park\",\"doi\":\"10.1145/2501511.2501518\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present Lytic, a domain-independent, faceted visual analytic (VA) system for interactive exploration of large datasets. It combines a flexible UI that adapts to arbitrary character-separated value (CSV) datasets with algorithmic preprocessing to compute unsupervised dimension reduction and cluster data from high-dimensional fields. It provides a variety of visualization options that require minimal user effort to configure and a consistent user experience between visualization types and underlying datasets. Filtering, comparison and visualization operations work in concert, allowing users to hop seamlessly between actions and pursue answers to expected and unexpected data hypotheses.\",\"PeriodicalId\":126062,\"journal\":{\"name\":\"Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2501511.2501518\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2501511.2501518","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lytic: synthesizing high-dimensional algorithmic analysis with domain-agnostic, faceted visual analytics
We present Lytic, a domain-independent, faceted visual analytic (VA) system for interactive exploration of large datasets. It combines a flexible UI that adapts to arbitrary character-separated value (CSV) datasets with algorithmic preprocessing to compute unsupervised dimension reduction and cluster data from high-dimensional fields. It provides a variety of visualization options that require minimal user effort to configure and a consistent user experience between visualization types and underlying datasets. Filtering, comparison and visualization operations work in concert, allowing users to hop seamlessly between actions and pursue answers to expected and unexpected data hypotheses.