{"id":"https://openalex.org/W4205444265","doi":"https://doi.org/10.1109/bigdata52589.2021.9671760","title":"Active Learning for the Subgraph Matching Problem","display_name":"Active Learning for the Subgraph Matching Problem","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4205444265","doi":"https://doi.org/10.1109/bigdata52589.2021.9671760"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671760","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010280134","display_name":"Yurun Ge","orcid":"https://orcid.org/0000-0001-9666-9988"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yurun Ge","raw_affiliation_strings":["Department of Mathematics, University of California, Los Angeles, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of California, Los Angeles, Los Angeles, CA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090707978","display_name":"Andrea L. Bertozzi","orcid":"https://orcid.org/0000-0003-0396-7391"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea L. Bertozzi","raw_affiliation_strings":["Department of Mathematics, University of California, Los Angeles, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of California, Los Angeles, Los Angeles, CA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2641","last_page":"2649"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.733269989490509},{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.6693116426467896},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5563209652900696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.525132417678833},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5127564668655396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4997425079345703},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4645046889781952},{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.45704370737075806},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.4483005404472351},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.43712037801742554},{"id":"https://openalex.org/keywords/analogy","display_name":"Analogy","score":0.41468796133995056},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13301414251327515}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.733269989490509},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.6693116426467896},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5563209652900696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.525132417678833},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5127564668655396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4997425079345703},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4645046889781952},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.45704370737075806},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.4483005404472351},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.43712037801742554},{"id":"https://openalex.org/C521332185","wikidata":"https://www.wikidata.org/wiki/Q185816","display_name":"Analogy","level":2,"score":0.41468796133995056},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13301414251327515},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671760","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:escholarship.org:ark:/13030/qt38d7s7c3","is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/38d7s7c3","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"etd"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W772516776","https://openalex.org/W1217907795","https://openalex.org/W1556806542","https://openalex.org/W1872312298","https://openalex.org/W1970125297","https://openalex.org/W1993615002","https://openalex.org/W2010532254","https://openalex.org/W2014219430","https://openalex.org/W2022739485","https://openalex.org/W2035173902","https://openalex.org/W2036400208","https://openalex.org/W2042932437","https://openalex.org/W2046968552","https://openalex.org/W2065982363","https://openalex.org/W2100586946","https://openalex.org/W2119157804","https://openalex.org/W2126359798","https://openalex.org/W2127816222","https://openalex.org/W2143163611","https://openalex.org/W2143363350","https://openalex.org/W2147405597","https://openalex.org/W2157958821","https://openalex.org/W2163184742","https://openalex.org/W2164279585","https://openalex.org/W2164952701","https://openalex.org/W2167058518","https://openalex.org/W2423652555","https://openalex.org/W2536223907","https://openalex.org/W2557654849","https://openalex.org/W2608355501","https://openalex.org/W2613146847","https://openalex.org/W2795050613","https://openalex.org/W2795196889","https://openalex.org/W2913192763","https://openalex.org/W2914584435","https://openalex.org/W2947160515","https://openalex.org/W2948437140","https://openalex.org/W2951786554","https://openalex.org/W2963749288","https://openalex.org/W2970380104","https://openalex.org/W3008765698","https://openalex.org/W3008959778","https://openalex.org/W3020919495","https://openalex.org/W3025380722","https://openalex.org/W3042669101","https://openalex.org/W3124443731","https://openalex.org/W3126784804","https://openalex.org/W3136667035","https://openalex.org/W4205145191","https://openalex.org/W4206723194","https://openalex.org/W6639393196","https://openalex.org/W6678881507","https://openalex.org/W6735374517","https://openalex.org/W6762949792"],"related_works":["https://openalex.org/W2392206215","https://openalex.org/W2365201483","https://openalex.org/W2355561779","https://openalex.org/W2352407775","https://openalex.org/W108701362","https://openalex.org/W2186567693","https://openalex.org/W2469799552","https://openalex.org/W2768582344","https://openalex.org/W28964973","https://openalex.org/W2615704157"],"abstract_inverted_index":{"The":[0],"subgraph":[1,63,77,197,283],"matching":[2,64,78,198,284],"problem":[3,75,161,183,194,199],"arises":[4],"in":[5,46,184,200,232,235],"a":[6,116,121,144,248,305,310],"variety":[7,249],"of":[8,17,97,124,159,250,262,272],"domains":[9],"including":[10],"pattern":[11],"recognition":[12],"for":[13,31,76,86,90,103,195,278,298,318],"segmented":[14],"images,":[15],"meshes":[16],"3D":[18],"objects,":[19],"biochemical":[20],"reactions,":[21],"and":[22,25,44,66,80,100,119,138,162,281,290],"security":[23],"applications.Large":[24],"complex":[26],"solution":[27,69,141,219],"spaces":[28],"are":[29,227],"common":[30],"this":[32,53,174,255,273],"graph-based":[33,316],"problem,":[34],"especially":[35],"when":[36,104],"the":[37,49,62,68,82,91,129,136,140,157,160,179,196,216,233,263,319],"world":[38,292],"graph":[39],"contains":[40],"many":[41],"more":[42,112],"nodes":[43,208,226,300],"edges":[45],"comparison":[47],"to":[48,60,110,126,134,151,155,168,172,178,214,301],"template":[50,206],"graph.":[51],"Overall,":[52],"dissertation":[54],"covers":[55],"three":[56],"parts:":[57],"using":[58],"symmetry":[59,137],"boost":[61],"algorithm":[65,203],"compress":[67,139],"space;":[70],"presenting":[71],"an":[72,191,202,236],"active":[73,87,181,192,264],"learning":[74,182,186,193,265],"problem;":[79],"discussing":[81],"different":[83,245,295],"quantitative":[84,296],"strategies":[85,246],"learning.":[88],"As":[89],"symmetry,":[92],"we":[93,189],"introduce":[94,304],"rigorous":[95,259],"definitions":[96,261],"structural":[98],"equivalence":[99],"establish":[101],"conditions":[102],"it":[105],"can":[106],"be":[107,132,211],"safely":[108],"used":[109],"generate":[111],"solutions.We":[113],"then":[114,228],"adapt":[115],"state-of-the-art":[117],"solver":[118],"perform":[120],"comprehensive":[122],"series":[123],"tests":[125],"demonstrate":[127],"how":[128,171],"Venn-diagram":[130],"could":[131],"applied":[133],"visualize":[135],"space.":[142,220],"Next,":[143],"real":[145,291],"use-case":[146],"scenario":[147],"may":[148],"require":[149],"analysts":[150,169],"query":[152],"additional":[153],"information":[154,222],"reduce":[156,215],"complexity":[158],"there":[163],"is":[164],"currently":[165],"little":[166],"guidance":[167],"on":[170,247,309],"optimize":[173],"choice.":[175],"By":[176],"analogy":[177],"well-known":[180],"machine":[185],"classification":[187],"problems,":[188],"present":[190,240,275],"which":[201],"suggests":[204],"optimal":[205],"target":[207,225],"that":[209,313],"would":[210],"most":[212],"likely":[213],"overly":[217],"large":[218],"Additional":[221],"about":[223],"those":[224],"acquired":[229],"from":[230,287],"humans":[231],"loop,":[234],"iterative":[237],"process.":[238],"We":[239,252,267,303],"some":[241],"case":[242],"studies":[243],"illustrating":[244],"datasets.":[251,321],"further":[253],"develop":[254],"idea":[256],"by":[257],"introducing":[258],"mathematical":[260],"problem.":[266],"also":[268],"prove":[269],"NP":[270],"completeness":[271],"problem.We":[274],"numerical":[276],"experiments":[277],"single":[279],"channel":[280],"multichannel":[282,320],"problems":[285],"created":[286],"both":[288],"synthetic":[289],"datasets.\\nWe":[293],"compare":[294],"criteria":[297,317],"choosing":[299],"query.":[302],"new":[306],"method":[307],"based":[308],"spanning":[311],"tree":[312],"outperforms":[314],"other":[315]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}