Keyword-centric community search

Zhiwei ZHANG, Xin HUANG, Jianliang XU, Koon Kau CHOI, Zechao Shang

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

Community search that finds only the communities pertaining to the query input has been widely studied from simple graphs to attributed graphs. However, a significant limitation of previous studies is that they all require the input of query nodes, which makes it difficult for users to specify exact queries if they are unfamiliar with the queried graph. To address this issue, in this paper we study a novel problem of keyword-centric community search (KCCS) over attributed graphs. In contrast to prior studies, no query nodes, but only query keywords, need to be specified to discover relevant communities. Specifically, given an attributed graph G, a query Q consisting of query keywords WQ, and an integer k, KCCS serves to find the largest subgraph of k-core of G that achieves the strongest keyword closeness w.r.t. WQ. We design a new function of keyword closeness and propose efficient algorithms to solve the KCCS problem. Furthermore, a novel core-based inverted index is developed to optimize performance. Extensive experiments on large real networks demonstrate that our solutions are more than three times faster than the baseline approach, and can find cohesive communities closely related to the query keywords.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
PublisherIEEE Computer Society
Pages422-433
Number of pages12
ISBN (Electronic)9781538674741
DOIs
Publication statusPublished - Apr 2019
Event35th IEEE International Conference on Data Engineering, ICDE 2019 - Macau, China
Duration: 8 Apr 201911 Apr 2019

Publication series

NameProceedings - International Conference on Data Engineering
Volume2019-April
ISSN (Print)1084-4627

Conference

Conference35th IEEE International Conference on Data Engineering, ICDE 2019
Country/TerritoryChina
CityMacau
Period8/04/1911/04/19

Scopus Subject Areas

  • Software
  • Signal Processing
  • Information Systems

User-Defined Keywords

  • Attributed graph
  • Community search
  • Key-word-centric

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