Mining frequent patterns in evolving graphs

Cigdem Aslay, Muhammad Anis Uddin Nasir, Gianmarco De Francisci Morales, Aristides Gionis

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

11 Citations (Scopus)

Abstract

Given a labeled graph, the frequent-subgraph mining (FSM) problem asks to find all the k-vertex subgraphs that appear with frequency greater than a given threshold. FSM has numerous applications ranging from biology to network science, as it provides a compact summary of the characteristics of the graph. However, the task is challenging, even more so for evolving graphs due to the streaming nature of the input and the exponential time complexity of the problem. In this paper, we initiate the study of the approximate FSM problem in both incremental and fully-dynamic streaming settings, where arbitrary edges can be added or removed from the graph. For each streaming setting, we propose algorithms that can extract a high-quality approximation of the frequent k-vertex subgraphs for a given threshold, at any given time instance, with high probability. In contrast to the existing state-of-the-art solutions that require iterating over the entire set of subgraphs for any update, our algorithms operate by maintaining a uniform sample of k-vertex subgraphs with optimized neighborhood-exploration procedures local to the updates. We provide theoretical analysis of the proposed algorithms and empirically demonstrate that the proposed algorithms generate high-quality results compared to baselines.

Original languageEnglish
Title of host publicationCIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management
EditorsNorman Paton, Selcuk Candan, Haixun Wang, James Allan, Rakesh Agrawal, Alexandros Labrinidis, Alfredo Cuzzocrea, Mohammed Zaki, Divesh Srivastava, Andrei Broder, Assaf Schuster
PublisherACM
Pages923-932
Number of pages10
ISBN (Electronic)9781450360142
DOIs
Publication statusPublished - 17 Oct 2018
MoE publication typeA4 Article in a conference publication
EventACM International Conference on Information and Knowledge Management - Torino, Italy
Duration: 22 Oct 201826 Oct 2018
Conference number: 27

Conference

ConferenceACM International Conference on Information and Knowledge Management
Abbreviated titleCIKM
Country/TerritoryItaly
CityTorino
Period22/10/201826/10/2018

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