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10.1145/2909132.2909246 http://scihub22266oqcxt.onion/10.1145/2909132.2909246 C5444304!5444304 !28553670     free     free     free Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\28553670 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       AVI 2016 ; 2016 (ä): 272-279 Nephropedia Template TP {{tp|p=28553670 |t=2016. VISAGE: Interactive Visual Graph Querying |pdf=|usr=}}{{28553670 }} gab.com Text VISAGE: Interactive Visual Graph Querying JO: AVI http://www.kidney.de/pget.php?&tw=1&pmid=28553670 #FOAvip 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 edges, achieving sub-second response times for common queries. Twit Text FOAVip VISAGE: Interactive Visual Graph Querying ????AVI http://www.kidney.de/pget.php?&tw=1&pmid=28553670 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28553670 #FOAvip English Wikipedia <ref>{{Cite pmid|28553670 }}</ref> VISAGE: Interactive Visual Graph Querying #MMPMID28553670 Pienta R ; Navathe S ; Tamersoy A ; Tong H ; Endert A ; Chau DH AVI 2016[Jun]; 2016 (ä): 272-279 PMID28553670 show ga 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 edges, achieving sub-second response times for common queries. äVISAGE: Interactive Visual Graph Querying (epmc).pdf DeepDyve Pubget Overpricing