TY - GEN
T1 - VISAGE
T2 - 13th ACM International Working Conference on Advanced Visual Interfaces, AVI 2016
AU - Pienta, Robert
AU - Tamersoy, Acar
AU - Endert, Alex
AU - Navathe, Shamkant
AU - Tong, Hanghang
AU - Ch, Duen Horng
N1 - Publisher Copyright:
© 2016 Copyright held by the owner/author(s).
PY - 2016/6/7
Y1 - 2016/6/7
N2 - Extracting useful patterns from large network datasets has become a fundamental challenge in many domains. We present VISAGE, an interactive visual graph querying approach that empowers users to construct expressive queries, without writing complex code (e.g., finding money laundering rings of bankers and business owners). Our contributions are as follows: (1) we introduce graph autocomplete, an interactive approach that guides users to construct and refine queries, preventing over-specification; (2) VISAGE guides the construction of graph queries using a data-driven approach, enabling users to specify queries with varying levels of specificity, from concrete and detailed (e.g., query by example), to abstract (e.g., with "wildcard" nodes of any types), to purely structural matching; (3) a twelve-participant, within-subject user study demonstrates VISAGE's ease of use and the ability to construct graph queries significantly faster than using a conventional query language; (4) VISAGE works on real graphs with over 468K.
AB - Extracting useful patterns from large network datasets has become a fundamental challenge in many domains. We present VISAGE, an interactive visual graph querying approach that empowers users to construct expressive queries, without writing complex code (e.g., finding money laundering rings of bankers and business owners). Our contributions are as follows: (1) we introduce graph autocomplete, an interactive approach that guides users to construct and refine queries, preventing over-specification; (2) VISAGE guides the construction of graph queries using a data-driven approach, enabling users to specify queries with varying levels of specificity, from concrete and detailed (e.g., query by example), to abstract (e.g., with "wildcard" nodes of any types), to purely structural matching; (3) a twelve-participant, within-subject user study demonstrates VISAGE's ease of use and the ability to construct graph queries significantly faster than using a conventional query language; (4) VISAGE works on real graphs with over 468K.
KW - Graph querying and mining
KW - Interaction design
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=84977109368&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84977109368&partnerID=8YFLogxK
U2 - 10.1145/2909132.2909246
DO - 10.1145/2909132.2909246
M3 - Conference contribution
AN - SCOPUS:84977109368
T3 - Proceedings of the Workshop on Advanced Visual Interfaces AVI
SP - 272
EP - 279
BT - AVI 2016 - Proceedings of the 2016 International Working Conference on Advanced Visual Interfaces
A2 - Buono, Paolo
A2 - Lanzilotti, Rosa
A2 - Matera, Maristella
PB - Association for Computing Machinery
Y2 - 7 June 2016 through 10 June 2016
ER -