MIDAS: Towards Efficient and Effective Maintenance of Canned Patterns in Visual Graph Query Interfaces

Kai Huang, Huey Eng Chua, Sourav S Bhowmick, Byron Choi, Shuigeng Zhou

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

1 Citation (Scopus)

Abstract

Several visual graph query interfaces (a.k.a gui) expose a set of canned patterns (i.e., small subgraph patterns) to expedite subgraph query formulation by enabling pattern-at-a-time construction. Unfortunately, manual generation of canned patterns is not only labour intensive but also may lack diversity to support efficient visual formulation of a wide range of subgraph queries. Recent efforts have taken a data-driven approach to select high-quality canned patterns for a gui automatically from the underlying graph database. However, as the underlying database evolves, these selected patterns may become stale and adversely impact efficient query formulation. In this paper, we present a novel framework called Midas for efficient and effective maintenance of the canned patterns as the database evolves. Specifically, it adopts a selective maintenance strategy that guarantees progressive gain of coverage of the patterns without sacrificing their diversity and cognitive load. Experimental study with real-world datasets and visual graph interfaces demonstrates the effectiveness of Midas compared to static guis.
Original languageEnglish
Title of host publicationSIGMOD '21: Proceedings of the 2021 International Conference on Management of Data
EditorsGuoliang Li, Zhanhuai Li
PublisherAssociation for Computing Machinery (ACM)
Pages764–776
Number of pages13
Edition1st
ISBN (Print)9781450383431
DOIs
Publication statusPublished - Jun 2021
EventACM SIGMOD International Conference on Management of Data, SIGMOD 2021 - Virtual, Online, China
Duration: 20 Jun 202125 Jun 2021

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

ConferenceACM SIGMOD International Conference on Management of Data, SIGMOD 2021
Country/TerritoryChina
CityVirtual, Online
Period20/06/2125/06/21

Scopus Subject Areas

  • Software
  • Information Systems

User-Defined Keywords

  • canned patterns
  • cognitive load
  • coverage
  • database updates
  • diversity
  • pattern maintenance
  • query formulation
  • visual graph query interfaces

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