Duen Horng Chau, C. Faloutsos, Hanghang Tong, Jason I. Hong, Brian Gallagher, Tina Eliassi-Rad
{"title":"GRAPHITE: A Visual Query System for Large Graphs","authors":"Duen Horng Chau, C. Faloutsos, Hanghang Tong, Jason I. Hong, Brian Gallagher, Tina Eliassi-Rad","doi":"10.1109/ICDMW.2008.99","DOIUrl":null,"url":null,"abstract":"We present Graphite, a system that allows the user to visually construct a query pattern, finds both its exact and approximate matching subgraphs in large attributed graphs, and visualizes the matches. For example, in a social network where a person's occupation is an attribute, the user can draw a 'star' query for \"finding a CEO who has interacted with a Secretary, a Manager, and an Accountant, or a structure very similar to this\". Graphite uses the G-Ray algorithm to run the query against a user-chosen data graph, gaining all of its benefits, namely its high speed, scalability, and its ability to find both exact and near matches. Therefore, for the example above, Graphite tolerates indirect paths between, say, the CEO and the Accountant, when no direct path exists. Graphite uses fast algorithms to estimate node proximities when finding matches, enabling it to scale well with the graph database size.We demonstrate Graphitepsilas usage and benefits using the DBLP author-publication graph, which consists of 356 K nodes and 1.9 M edges. A demo video of Graphite can be downloaded at http://www.cs.cmu.edu/~dchau/graphite/graphite.mov.","PeriodicalId":175955,"journal":{"name":"2008 IEEE International Conference on Data Mining Workshops","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"54","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Data Mining Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2008.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 54
Abstract
We present Graphite, a system that allows the user to visually construct a query pattern, finds both its exact and approximate matching subgraphs in large attributed graphs, and visualizes the matches. For example, in a social network where a person's occupation is an attribute, the user can draw a 'star' query for "finding a CEO who has interacted with a Secretary, a Manager, and an Accountant, or a structure very similar to this". Graphite uses the G-Ray algorithm to run the query against a user-chosen data graph, gaining all of its benefits, namely its high speed, scalability, and its ability to find both exact and near matches. Therefore, for the example above, Graphite tolerates indirect paths between, say, the CEO and the Accountant, when no direct path exists. Graphite uses fast algorithms to estimate node proximities when finding matches, enabling it to scale well with the graph database size.We demonstrate Graphitepsilas usage and benefits using the DBLP author-publication graph, which consists of 356 K nodes and 1.9 M edges. A demo video of Graphite can be downloaded at http://www.cs.cmu.edu/~dchau/graphite/graphite.mov.