PICASSO: Exploratory search of connected subgraph substructures in graph databases

Kai Huang, Sourav S. Bhowmick, Shuigeng Zhou, Koon Kau CHOI

Research output: Contribution to journalConference articlepeer-review

11 Citations (Scopus)

Abstract

Recently, exploratory search has received much attention in information retrieval and database fields. This search paradigm assists users who do not have a clear search intent and are unfamiliar with the underlying data space. Specifically, query formulation evolves iteratively as the user becomes more familiar with the content. Despite its growing importance, exploratory search on graph-structured data has received little attention in the literature. We demonstrate a system called picasso to realize exploratory substructure search on a graph database containing a set of small or medium-sized data graphs. picasso embodies several novel features such as progressive (i.e., iterative) formulation of queries visually and incremental processing, multistream results exploration wall to visualize, explore, and analyze search results to identify possible search directions.

Original languageEnglish
Pages (from-to)1861-1864
Number of pages4
JournalProceedings of the VLDB Endowment
Volume10
Issue number12
DOIs
Publication statusPublished - 1 Aug 2017
Event43rd International Conference on Very Large Data Bases, VLDB 2017 - Munich, Germany
Duration: 28 Aug 20171 Sep 2017

Scopus Subject Areas

  • Computer Science (miscellaneous)
  • Computer Science(all)

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