BOOMER: A Tool for Blending Visual P-Homomorphic Queries on Large Networks

Yinglong Song, Huey Eng Chua, Sourav S. Bhowmick, Byron Koon Kau Choi, Shuigeng Zhou

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

1 Citation (Scopus)

Abstract

The paradigm of interleaving (i.e. blending) visual subgraph query formulation and processing by exploiting the latency offered by the GUI brings in several potential benefits such as superior system response time (SRT) and opportunities to enhance usability of graph databases. Recent efforts at implementing this paradigm are focused on subgraph isomorphism-based queries, which are often restrictive in many real-world graph applications. In this demonstration, we present a novel system called BOOMER to realize this paradigm on more generic but complex bounded 1-1 p-homomorphic(BPH) queries on large networks. Intuitively, a BPH query maps an edge of the query to bounded paths in the data graph. We demonstrate various innovative features of BOOMER, its flexibility, and its promising performance.

Original languageEnglish
Title of host publicationSIGMOD '20: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
PublisherAssociation for Computing Machinery (ACM)
Pages2685-2688
Number of pages4
ISBN (Print)9781450367356
DOIs
Publication statusPublished - 11 Jun 2020
EventACM SIGMOD International Conference on Management of Data, SIGMOD 2020 - Portland, United States
Duration: 14 Jun 202019 Jun 2020
https://dl.acm.org/doi/proceedings/10.1145/3318464

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 2020
Country/TerritoryUnited States
CityPortland
Period14/06/2019/06/20
Internet address

Scopus Subject Areas

  • Software
  • Information Systems

User-Defined Keywords

  • blending
  • cap index
  • graph query results visualization
  • p-homomorphic query
  • visual graph query formulation

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