{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,3]],"date-time":"2025-05-03T23:07:01Z","timestamp":1746313621055},"reference-count":44,"publisher":"Association for Computing Machinery (ACM)","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2021,7]]},"abstract":"<jats:p>\n            <jats:italic>Canned patterns<\/jats:italic>\n            (\n            <jats:italic>i.e.<\/jats:italic>\n            , small subgraph patterns) in visual graph query interfaces (a.k.a GUI) facilitate efficient query formulation by enabling\n            <jats:italic>pattern-at-a-time<\/jats:italic>\n            construction mode. However, existing GUIS for querying large networks either do not expose any canned patterns or if they do then they are typically selected manually based on domain knowledge. Unfortunately, manual generation of canned patterns is not only labor intensive but may also lack diversity for supporting efficient visual formulation of a wide range of subgraph queries. In this paper, we present a novel, generic, and extensible framework called TATTOO that takes a data-driven approach to\n            <jats:italic>automatically<\/jats:italic>\n            select canned patterns for a GUI from large networks. Specifically, it first\n            <jats:italic>decomposes<\/jats:italic>\n            the underlying network into\n            <jats:italic>truss-infested<\/jats:italic>\n            and\n            <jats:italic>truss-oblivious<\/jats:italic>\n            regions. Then\n            <jats:italic>candidate<\/jats:italic>\n            canned patterns capturing different real-world query topologies are generated from these regions. Canned patterns based on a user-specified\n            <jats:italic>plug<\/jats:italic>\n            are then\n            <jats:italic>selected<\/jats:italic>\n            for the GUI from these candidates by maximizing\n            <jats:italic>coverage<\/jats:italic>\n            and\n            <jats:italic>diversity<\/jats:italic>\n            , and by minimizing the\n            <jats:italic>cognitive load<\/jats:italic>\n            of the pattern set. Experimental studies with real-world datasets demonstrate the benefits of TATTOO. Importantly, this work takes a concrete step towards realizing\n            <jats:italic>plug-and-play<\/jats:italic>\n            visual graph query interfaces for large networks.\n          <\/jats:p>","DOI":"10.14778\/3476249.3476256","type":"journal-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T16:46:23Z","timestamp":1635353183000},"page":"1979-1991","source":"Crossref","is-referenced-by-count":11,"title":["Towards plug-and-play visual graph query interfaces"],"prefix":"10.14778","volume":"14","author":[{"given":"Zifeng","family":"Yuan","sequence":"first","affiliation":[{"name":"Fudan University &amp; NTU"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huey Eng","family":"Chua","sequence":"additional","affiliation":[{"name":"Nanyang Technological University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sourav S","family":"Bhowmick","sequence":"additional","affiliation":[{"name":"Nanyang Technological University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zekun","family":"Ye","sequence":"additional","affiliation":[{"name":"Fudan University &amp; NTU"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wook-Shin","family":"Han","sequence":"additional","affiliation":[{"name":"POSTECH"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Byron","family":"Choi","sequence":"additional","affiliation":[{"name":"Hong Kong Baptist University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,10,27]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2021. 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