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MOSS-5: A fast method of approximating counts of 5-node graphlets in large graphs (extended abstract)

  • King Abdullah University of Science and Technology
  • Huawei Technologies Co., Ltd.
  • Tencent
  • Chinese University of Hong Kong
  • University of Massachusetts
  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

Despite recent efforts in counting 3-node and 4-node graphlets, little attention has been paid to characterizing 5-node graphlets. In this paper, we develop a computationally efficient sampling method to estimate 5-node graphlet counts. We not only provide a fast sampling method and unbiased estimators of graphlet counts, but also derive simple yet exact formulas for the variances of the estimators which are of great value in practice-the variances can be used to bound the estimates' errors and determine the smallest necessary sampling budget for a desired accuracy. We conduct experiments on a variety of real-world datasets, and the results show that our method is several orders of magnitude faster than the state-of-The-Art methods with the same accuracy.

源语言英语
主期刊名Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
出版商Institute of Electrical and Electronics Engineers Inc.
1773-1774
页数2
ISBN(电子版)9781538655207
DOI
出版状态已出版 - 24 10月 2018
活动34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, 法国
期限: 16 4月 201819 4月 2018

出版系列

姓名Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

会议

会议34th IEEE International Conference on Data Engineering, ICDE 2018
国家/地区法国
Paris
时期16/04/1819/04/18

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