@inproceedings{b54e9678ea8d49179ab33efa1669d594,
title = "Compressing streaming graph data based on triangulation",
abstract = "There is a wide diversity of applications for graph compression in web data management, scientific data processing, and social data analysis. In real-life applications like social media data processing, elements in a graph, typically vertices and edges, are arriving continuously. Compressing the graph before storing it in a database is important for real-time processing and analysis, while being a challenging yet interesting problem. A streaming lossless compression method, named as STT (streaming timeliness triangulation), is introduced in this paper. It is a time-efficient method for compressing a streaming graph, which differs itself from static graph compression methods in that: (1) it{\textquoteright}s able to compress streaming graph without occupying extra storage; (2) it can achieve both low compression ratio and high throughput over the streaming graph; (3) it supports efficient graph query processing directly over compressed graphs. Thus, it can support a wide range of streaming graph processing tasks. Empirical study over a paper co-author graph and a real-life large-scale social network graph has shown the superiority of the newly proposed method over existing static graph compression methods.",
keywords = "Graph compression, Graph query, Social graph, Streaming data",
author = "Liang Zhang and Ming Gao and Weining Qian and Aoying Zhou",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 18th International Conference on Web Technologies and Applications, APWeb 2016 and Workshop on 2nd International Workshop on Web Data Mining and Applications, WDMA 2016 and 1st International Workshop on Graph Analytics and Query Processing, GAP 2016 and 1st International Workshop on Spatial-temporal Data Management and Analytics, SDMA 2016 ; Conference date: 23-09-2016 Through 25-09-2016",
year = "2016",
doi = "10.1007/978-3-319-45835-9\_15",
language = "英语",
isbn = "9783319458342",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "164--175",
editor = "Jia Zhu and Rong Zhang and Lijun Chang and Wenjie Zhang and Kuien Liu and Atsuyuki Morishima and Fu, \{Tom Z.J.\} and Xiaoyan Yang and Zhiwei Zhang",
booktitle = "Web Technologies and Applications - APWeb 2016 Workshops, WDMA, GAP, and SDMA, Proceedings",
address = "德国",
}