A parameter-free approach to lossless summarization of fully dynamic graphs
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Kenli Li | Zhibang Yang | Jianye Yang | Ziyi Ma | Yuling Liu
[1] Kuan-Ching Li,et al. Efficient Distributed Approaches to Core Maintenance on Large Dynamic Graphs , 2022, IEEE Transactions on Parallel and Distributed Systems.
[2] Wenjie Zhang,et al. (p,q)-biclique counting and enumeration for large sparse bipartite graphs , 2021, The VLDB Journal.
[3] Shaojie Tang,et al. Best Bang for the Buck: Cost-Effective Seed Selection for Online Social Networks , 2020, IEEE Transactions on Knowledge and Data Engineering.
[4] Ying Zhang,et al. Exploring Cohesive Subgraphs with Vertex Engagement and Tie Strength in Bipartite Graphs , 2020, Inf. Sci..
[5] Lei Chen,et al. Efficient Graph Query Processing over Geo-Distributed Datacenters , 2020, SIGIR.
[6] Kijung Shin,et al. Incremental Lossless Graph Summarization , 2020, KDD.
[7] Kijung Shin,et al. SSumM: Sparse Summarization of Massive Graphs , 2020, KDD.
[8] Chen Chen,et al. Reachability preserving compression for dynamic graph , 2020, Inf. Sci..
[9] Ying Zhang,et al. Distributed Streaming Set Similarity Join , 2020, 2020 IEEE 36th International Conference on Data Engineering (ICDE).
[10] Yao Ge,et al. Labeled graph sketches: Keeping up with real-time graph streams , 2019, Inf. Sci..
[11] Hema Raghavan,et al. SWeG: Lossless and Lossy Summarization of Web-Scale Graphs , 2019, WWW.
[12] Yunjun Gao,et al. Efficient and Incremental Clustering Algorithms on Star-Schema Heterogeneous Graphs , 2019, 2019 IEEE 35th International Conference on Data Engineering (ICDE).
[13] Kenli Li,et al. FlinkCL: An OpenCL-Based In-Memory Computing Architecture on Heterogeneous CPU-GPU Clusters for Big Data , 2018, IEEE Transactions on Computers.
[14] Petros Efstathopoulos,et al. Utility-Driven Graph Summarization , 2018, Proc. VLDB Endow..
[15] Sorour E. Amiri,et al. Efficiently summarizing attributed diffusion networks , 2018, Data Mining and Knowledge Discovery.
[16] Diego R. Amancio,et al. Extractive Multi-document Summarization Using Multilayer Networks , 2017, Physica A: Statistical Mechanics and its Applications.
[17] Sourav S. Bhowmick,et al. Summarizing Static and Dynamic Big Graphs , 2017, Proc. VLDB Endow..
[18] LinXuemin,et al. Top-k spatial-keyword publish/subscribe over sliding window , 2017, VLDB 2017.
[19] Young-Koo Lee,et al. Set-based unified approach for summarization of a multi-attributed graph , 2017, World Wide Web.
[20] Cesar H. Comin,et al. Connecting network science and information theory , 2017, Physica A: Statistical Mechanics and its Applications.
[21] Danai Koutra,et al. Graph Summarization Methods and Applications , 2016, ACM Comput. Surv..
[22] Ricardo Baeza-Yates,et al. Scalable dynamic graph summarization , 2016, 2016 IEEE International Conference on Big Data (Big Data).
[23] Yinghui Wu,et al. Mining Summaries for Knowledge Graph Search , 2018, IEEE Transactions on Knowledge and Data Engineering.
[24] Christian S. Jensen,et al. Efficient Online Summarization of Large-Scale Dynamic Networks , 2016, IEEE Transactions on Knowledge and Data Engineering.
[25] Ming Gao,et al. Compressing Streaming Graph Data Based on Triangulation , 2016, APWeb Workshops.
[26] Charu C. Aggarwal,et al. Query-friendly compression of graph streams , 2016, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[27] Francesco Bonchi,et al. Graph summarization with quality guarantees , 2014, 2014 IEEE International Conference on Data Mining.
[28] Diego R. Amancio,et al. Word sense disambiguation via high order of learning in complex networks , 2012, ArXiv.
[29] Nisheeth Shrivastava,et al. Graph summarization with bounded error , 2008, SIGMOD Conference.
[30] Kenli Li,et al. A Parameter-Free Approach for Lossless Streaming Graph Summarization , 2021, International Conference on Database Systems for Advanced Applications.