{"title":"持久图表示的空间高效方案","authors":"Stavros Kontopoulos, G. Drakopoulos","doi":"10.1109/ICTAI.2014.52","DOIUrl":null,"url":null,"abstract":"Graph mining is currently the focus of intense research. Major driving factors include social media, opinion mining, and the schemaless noSQL databases. Time evolving or dynamic graphs are the primary data structures in these fields. Often dynamic graphs must support persistency, meaning that from any given graph state past states can be accessed. Within the graph database context, persistency enables rollback capability, whereas in social media several phenomena such as friend deletion can be modeled. A novel, efficient, and persistent data structure based on tries is proposed. Its potential is displayed by added persistency to the deterministic Kronecker graph model.","PeriodicalId":142794,"journal":{"name":"2014 IEEE 26th International Conference on Tools with Artificial Intelligence","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"A Space Efficient Scheme for Persistent Graph Representation\",\"authors\":\"Stavros Kontopoulos, G. Drakopoulos\",\"doi\":\"10.1109/ICTAI.2014.52\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Graph mining is currently the focus of intense research. Major driving factors include social media, opinion mining, and the schemaless noSQL databases. Time evolving or dynamic graphs are the primary data structures in these fields. Often dynamic graphs must support persistency, meaning that from any given graph state past states can be accessed. Within the graph database context, persistency enables rollback capability, whereas in social media several phenomena such as friend deletion can be modeled. A novel, efficient, and persistent data structure based on tries is proposed. Its potential is displayed by added persistency to the deterministic Kronecker graph model.\",\"PeriodicalId\":142794,\"journal\":{\"name\":\"2014 IEEE 26th International Conference on Tools with Artificial Intelligence\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 26th International Conference on Tools with Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTAI.2014.52\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 26th International Conference on Tools with Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTAI.2014.52","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Space Efficient Scheme for Persistent Graph Representation
Graph mining is currently the focus of intense research. Major driving factors include social media, opinion mining, and the schemaless noSQL databases. Time evolving or dynamic graphs are the primary data structures in these fields. Often dynamic graphs must support persistency, meaning that from any given graph state past states can be accessed. Within the graph database context, persistency enables rollback capability, whereas in social media several phenomena such as friend deletion can be modeled. A novel, efficient, and persistent data structure based on tries is proposed. Its potential is displayed by added persistency to the deterministic Kronecker graph model.
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