{"title":"非结构化稀疏图表示的复杂性","authors":"Martin Nehéz, Peter Bartalos","doi":"10.1145/3351556.3351576","DOIUrl":null,"url":null,"abstract":"In this paper, we address the problem of the trade-off between the compact memory representation of graphs and their amount of randomness. We design a representation (abbreviated as DBP representation) which does not use information on the structure of graphs, hence it is generally usable. Based on our theoretical lower bound on graph space representation, we define a compression ratio for a given graph with respect to the DBP representation. Based on experimental results, we derive the empirical relationship between the amount of randomness and the compression ratio.","PeriodicalId":126836,"journal":{"name":"Proceedings of the 9th Balkan Conference on Informatics","volume":"28 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Complexity Aspects of Unstructured Sparse Graph Representation\",\"authors\":\"Martin Nehéz, Peter Bartalos\",\"doi\":\"10.1145/3351556.3351576\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we address the problem of the trade-off between the compact memory representation of graphs and their amount of randomness. We design a representation (abbreviated as DBP representation) which does not use information on the structure of graphs, hence it is generally usable. Based on our theoretical lower bound on graph space representation, we define a compression ratio for a given graph with respect to the DBP representation. Based on experimental results, we derive the empirical relationship between the amount of randomness and the compression ratio.\",\"PeriodicalId\":126836,\"journal\":{\"name\":\"Proceedings of the 9th Balkan Conference on Informatics\",\"volume\":\"28 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 9th Balkan Conference on Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3351556.3351576\",\"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 9th Balkan Conference on Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3351556.3351576","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Complexity Aspects of Unstructured Sparse Graph Representation
In this paper, we address the problem of the trade-off between the compact memory representation of graphs and their amount of randomness. We design a representation (abbreviated as DBP representation) which does not use information on the structure of graphs, hence it is generally usable. Based on our theoretical lower bound on graph space representation, we define a compression ratio for a given graph with respect to the DBP representation. Based on experimental results, we derive the empirical relationship between the amount of randomness and the compression ratio.