FGreat: Focused graph query autocompletion

Nathan Ng, Peipei Yi, Zhiwei ZHANG, Koon Kau CHOI, Sourav S. Bhowmick, Jianliang XU

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

Abstract

Composing queries is evidently a tedious task. This is particularly true of graph queries as they are typically complex and prone to errors. This is compounded by the fact that graph schemas can be missing or too loose to be helpful for query formulation. Graph Query AutoCompletion (gQAC) alleviates users from the potentially painstaking task of graph query formulation. This demonstration presents an interactive visual Focused GRaph quEry AutocompleTion framework, called FGreat. Its novelty relies on the user focus for gQAC, which is a subgraph of the current query that a user is focusing on. FGreat automatically computes a focus and completes the query at the focus, as opposed to an arbitrary query subgraph. This demonstration presents two complementary approaches to compute the user focus for different circumstances. It computes the focus from either (i) the sequence of edges that a user recently added to his/her query, or (ii) the position of the mouse cursor, if it is available. We demonstrate that the user focus enhances both the effectiveness and efficiency of graph query autocompletion.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
PublisherIEEE Computer Society
Pages1956-1959
Number of pages4
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

  • Database usability
  • Graph autocompletion
  • Graphs
  • Subgraph query

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