TY - JOUR
T1 - PICASSO: exploratory search of connected subgraph substructures in graph databases
AU - Huang, Kai
AU - Bhowmick, Sourav S.
AU - Zhou, Shuigeng
AU - Choi, Byron Koon Kau
N1 - Funding Information:
Kai Huang and Sourav S Bhowmick are supported by the Singapore-MOE AcRF Tier-2 Grant MOE2015-T2-1-040. Shuigeng Zhou is funded by the Key Projects of Fundamental Research Program of Shanghai Municipal Commission of Science and Technology under grant No. 14JC1400300. Byron Choi is supported by HKRGC GRF 12201315 and 12232716.
PY - 2017/8
Y1 - 2017/8
N2 - 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.
AB - 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.
UR - http://vldb.org/pvldb/vol10-volume-info/
UR - http://www.scopus.com/inward/record.url?scp=85036625269&partnerID=8YFLogxK
U2 - 10.14778/3137765.3137794
DO - 10.14778/3137765.3137794
M3 - Conference article
AN - SCOPUS:85036625269
SN - 2150-8097
VL - 10
SP - 1861
EP - 1864
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 12
T2 - 43rd International Conference on Very Large Data Bases, VLDB 2017
Y2 - 28 August 2017 through 1 September 2017
ER -