{"id":"https://openalex.org/W2229578389","doi":"https://doi.org/10.1007/s10994-015-5539-3","title":"Subjective interestingness of subgraph patterns","display_name":"Subjective interestingness of subgraph patterns","publication_year":2016,"publication_date":"2016-01-07","ids":{"openalex":"https://openalex.org/W2229578389","doi":"https://doi.org/10.1007/s10994-015-5539-3","mag":"2229578389"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-015-5539-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-015-5539-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-015-5539-3.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-015-5539-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022646570","display_name":"Matthijs van Leeuwen","orcid":"https://orcid.org/0000-0002-0510-3549"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]},{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["BE","NL"],"is_corresponding":true,"raw_author_name":"Matthijs van Leeuwen","raw_affiliation_strings":["Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands","Machine Learning, Department of Computer Science, KU Leuven, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]},{"raw_affiliation_string":"Machine Learning, Department of Computer Science, KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076045275","display_name":"Tijl De Bie","orcid":"https://orcid.org/0000-0002-2692-7504"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]},{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE","GB"],"is_corresponding":false,"raw_author_name":"Tijl De Bie","raw_affiliation_strings":["Data Science Lab, Ghent University, Ghent, Belgium","Intelligent Systems Laboratory, University of Bristol, Bristol, UK"],"affiliations":[{"raw_affiliation_string":"Data Science Lab, Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Intelligent Systems Laboratory, University of Bristol, Bristol, UK","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032415055","display_name":"Eirini Spyropoulou","orcid":null},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Eirini Spyropoulou","raw_affiliation_strings":["Intelligent Systems Laboratory, University of Bristol, Bristol, UK"],"affiliations":[{"raw_affiliation_string":"Intelligent Systems Laboratory, University of Bristol, Bristol, UK","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082068867","display_name":"C\u00e9dric Mesnage","orcid":"https://orcid.org/0000-0002-2004-6378"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"C\u00e9dric Mesnage","raw_affiliation_strings":["Intelligent Systems Laboratory, University of Bristol, Bristol, UK"],"affiliations":[{"raw_affiliation_string":"Intelligent Systems Laboratory, University of Bristol, Bristol, UK","institution_ids":["https://openalex.org/I36234482"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022646570"],"corresponding_institution_ids":["https://openalex.org/I121797337","https://openalex.org/I99464096"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":6.9057,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.96604164,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"105","issue":"1","first_page":"41","last_page":"75"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10799","display_name":"Data Visualization and Analytics","score":0.9958000183105469,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6520845890045166},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6510047912597656},{"id":"https://openalex.org/keywords/concreteness","display_name":"Concreteness","score":0.5665340423583984},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.5214442610740662},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47732076048851013},{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.41826897859573364},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.405435174703598},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3151922821998596},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.09801554679870605}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6520845890045166},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6510047912597656},{"id":"https://openalex.org/C2778436841","wikidata":"https://www.wikidata.org/wiki/Q5159081","display_name":"Concreteness","level":2,"score":0.5665340423583984},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.5214442610740662},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47732076048851013},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.41826897859573364},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.405435174703598},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3151922821998596},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.09801554679870605},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1007/s10994-015-5539-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-015-5539-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-015-5539-3.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/529083","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/529083","pdf_url":null,"source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Machine Learning, vol. 105 (1), (41-75)","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:archive.ugent.be:8087155","is_oa":true,"landing_page_url":"https://biblio.ugent.be/publication/8087155","pdf_url":null,"source":{"id":"https://openalex.org/S4306400477","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"MACHINE LEARNING","raw_type":null},{"id":"pmh:oai:pure.atira.dk:publications/53b2aad4-8185-4363-a1cd-38549ddb1e38","is_oa":true,"landing_page_url":"https://pure.solent.ac.uk/en/publications/53b2aad4-8185-4363-a1cd-38549ddb1e38","pdf_url":null,"source":{"id":"https://openalex.org/S4306402589","display_name":"Solent University Research Portal (Solent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I156118397","host_organization_name":"Southampton Solent University","host_organization_lineage":["https://openalex.org/I156118397"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"van Leeuwen , M , De Bie , T , Spyropoulou , E & Mesnage , C 2016 , ' Subjective interestingness of subgraph patterns ' , Machine Learning , vol. 105 , no. 1 , pp. 41-75 . https://doi.org/10.1007/s10994-015-5539-3","raw_type":"article"},{"id":"pmh:oai:scholarlypublications.universiteitleiden.nl:item_2887936","is_oa":false,"landing_page_url":"https://hdl.handle.net/1887/47240","pdf_url":null,"source":{"id":"https://openalex.org/S4306400850","display_name":"Leiden Repository (Leiden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I121797337","host_organization_name":"Leiden University","host_organization_lineage":["https://openalex.org/I121797337"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning","raw_type":"Article / Letter to editor"},{"id":"pmh:ul:oai:scholarlypublications.universiteitleiden.nl:item_2887936","is_oa":true,"landing_page_url":"http://hdl.handle.net/1887/47240","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning, 105(1), 41 - 75. Springer Verlag (Germany)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s10994-015-5539-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-015-5539-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-015-5539-3.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2602915566","display_name":null,"funder_award_id":"EP/M000060/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G2988008325","display_name":"Data Science for the Detection of Emerging Music Styles","funder_award_id":"EP/M000060/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320321730","display_name":"Fonds Wetenschappelijk Onderzoek","ror":"https://ror.org/03qtxy027"},{"id":"https://openalex.org/F4320327336","display_name":"Vlaamse regering","ror":null},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320334678","display_name":"European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2229578389.pdf","grobid_xml":"https://content.openalex.org/works/W2229578389.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W66155912","https://openalex.org/W136742478","https://openalex.org/W181982077","https://openalex.org/W183656749","https://openalex.org/W1537786382","https://openalex.org/W1586552957","https://openalex.org/W1974067702","https://openalex.org/W1978036582","https://openalex.org/W1979462644","https://openalex.org/W1994432310","https://openalex.org/W1997585986","https://openalex.org/W2009723146","https://openalex.org/W2017109153","https://openalex.org/W2029237138","https://openalex.org/W2038902401","https://openalex.org/W2042587503","https://openalex.org/W2076743544","https://openalex.org/W2083524178","https://openalex.org/W2095293504","https://openalex.org/W2095952922","https://openalex.org/W2099111195","https://openalex.org/W2102297485","https://openalex.org/W2103012681","https://openalex.org/W2119757574","https://openalex.org/W2119878361","https://openalex.org/W2126106168","https://openalex.org/W2128366083","https://openalex.org/W2143211346","https://openalex.org/W2148606255","https://openalex.org/W2210387432","https://openalex.org/W2296319761","https://openalex.org/W4233413206","https://openalex.org/W4236765470","https://openalex.org/W4250589301","https://openalex.org/W4288080327","https://openalex.org/W6607484853","https://openalex.org/W6674851815"],"related_works":["https://openalex.org/W2532922352","https://openalex.org/W2604893261","https://openalex.org/W2915540008","https://openalex.org/W2361654510","https://openalex.org/W2128390795","https://openalex.org/W1482551403","https://openalex.org/W2604114816","https://openalex.org/W2954463587","https://openalex.org/W2152074130","https://openalex.org/W2393701947"],"abstract_inverted_index":{"The":[0,215],"utility":[1],"of":[2,11,43,72,106,134,149,221],"a":[3,8,12,22,49,77,87,93,128],"dense":[4,88,178,197],"subgraph":[5,89,179,198],"in":[6,17,34,114],"gaining":[7],"better":[9],"understanding":[10],"graph":[13],"has":[14,127,143],"been":[15],"formalised":[16],"numerous":[18],"ways,":[19],"each":[20],"striking":[21],"different":[23,161,227],"balance":[24],"between":[25],"approximating":[26],"actual":[27],"interestingness":[28,51,158,188,224],"and":[29,68,137,170,190,231],"computational":[30,41],"efficiency.":[31],"A":[32],"difficulty":[33,82],"making":[35],"this":[36,58,81,115],"trade-off":[37],"is":[38,46,52,61,74,100,160],"that,":[39],"while":[40],"cost":[42],"an":[44],"algorithm":[45],"relatively":[47],"well-defined,":[48],"pattern\u2019s":[50],"fundamentally":[53],"subjective.":[54],"This":[55],"means":[56],"that":[57,239],"latter":[59],"aspect":[60],"often":[62],"treated":[63],"only":[64,126],"informally":[65],"or":[66],"neglected,":[67],"instead":[69],"some":[70],"form":[71],"density":[73,133],"used":[75],"as":[76],"proxy.":[78],"We":[79,165],"resolve":[80],"by":[83],"formalising":[84],"what":[85],"makes":[86],"pattern":[90],"interesting":[91,177,237],"to":[92,181,195,201,212,235,244],"given":[94,226],"user.":[95],"Unsurprisingly,":[96],"the":[97,103,107,110,124,131,135,141,147,150,156,175,182,186,219,222],"resulting":[98,157],"measure":[99,159,189,225],"dependent":[101],"on":[102],"prior":[104,144,228],"beliefs":[105,145],"user":[108,125,142],"about":[109,130,146],"graph.":[111],"For":[112],"concreteness,":[113],"paper":[116],"we":[117,153],"consider":[118],"two":[119],"cases:":[120],"one":[121],"case":[122,139],"where":[123,140],"belief":[129,229],"overall":[132],"graph,":[136],"another":[138],"degrees":[148],"vertices.":[151],"Furthermore,":[152],"illustrate":[154],"how":[155],"from":[162],"previous":[163],"proposals.":[164],"also":[166],"propose":[167],"effective":[168],"exact":[169],"approximate":[171],"algorithms":[172],"for":[173],"mining":[174],"most":[176,202],"according":[180],"proposed":[183,187],"measure.":[184],"Usefully,":[185],"approach":[191],"lend":[192],"themselves":[193],"well":[194],"iterative":[196],"discovery.":[199],"Contrary":[200],"existing":[203],"approaches,":[204],"our":[205,232],"method":[206],"naturally":[207],"allows":[208],"subsequently":[209],"found":[210],"patterns":[211],"be":[213],"overlapping.":[214],"empirical":[216],"evaluation":[217],"highlights":[218],"properties":[220],"new":[223],"sets,":[230],"approach\u2019s":[233],"ability":[234],"find":[236],"subgraphs":[238],"other":[240],"methods":[241],"are":[242],"unable":[243],"find.":[245]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}