{"id":"https://openalex.org/W2118349699","doi":"https://doi.org/10.1109/icdm.2003.1250974","title":"Efficient mining of frequent subgraphs in the presence of isomorphism","display_name":"Efficient mining of frequent subgraphs in the presence of isomorphism","publication_year":2004,"publication_date":"2004-04-23","ids":{"openalex":"https://openalex.org/W2118349699","doi":"https://doi.org/10.1109/icdm.2003.1250974","mag":"2118349699"},"language":"en","primary_location":{"id":"doi:10.1109/icdm.2003.1250974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","raw_type":"proceedings-article"},"type":"article","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/A5080409305","display_name":"Jun Huan","orcid":"https://orcid.org/0000-0002-7020-1604"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]},{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"J. Huan","raw_affiliation_strings":["Department of Computer Science, North Carolina State University, Chapel Hill, USA","Dept. of Comput. Sci., North Carolina Univ., Chapel Hill, NC, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, North Carolina State University, Chapel Hill, USA","institution_ids":["https://openalex.org/I137902535"]},{"raw_affiliation_string":"Dept. of Comput. Sci., North Carolina Univ., Chapel Hill, NC, USA#TAB#","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100392089","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-8180-2886"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]},{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W. Wang","raw_affiliation_strings":["Department of Computer Science, North Carolina State University, Chapel Hill, USA","Dept. of Comput. Sci., North Carolina Univ., Chapel Hill, NC, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, North Carolina State University, Chapel Hill, USA","institution_ids":["https://openalex.org/I137902535"]},{"raw_affiliation_string":"Dept. of Comput. Sci., North Carolina Univ., Chapel Hill, NC, USA#TAB#","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011567934","display_name":"Jan F. Prins","orcid":"https://orcid.org/0000-0003-0853-6099"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]},{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Prins","raw_affiliation_strings":["Department of Computer Science, North Carolina State University, Chapel Hill, USA","Dept. of Comput. Sci., North Carolina Univ., Chapel Hill, NC, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, North Carolina State University, Chapel Hill, USA","institution_ids":["https://openalex.org/I137902535"]},{"raw_affiliation_string":"Dept. of Comput. Sci., North Carolina Univ., Chapel Hill, NC, USA#TAB#","institution_ids":["https://openalex.org/I114027177"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080409305"],"corresponding_institution_ids":["https://openalex.org/I114027177","https://openalex.org/I137902535"],"apc_list":null,"apc_paid":null,"fwci":83.1697,"has_fulltext":false,"cited_by_count":616,"citation_normalized_percentile":{"value":0.99926588,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"549","last_page":"552"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":1.0,"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":1.0,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9969000220298767,"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/T11106","display_name":"Data Management and Algorithms","score":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.8916818499565125},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.7238595485687256},{"id":"https://openalex.org/keywords/cheminformatics","display_name":"Cheminformatics","score":0.7051172256469727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6877117156982422},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5286983251571655},{"id":"https://openalex.org/keywords/graph-database","display_name":"Graph database","score":0.516293466091156},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5151978135108948},{"id":"https://openalex.org/keywords/graph-factorization","display_name":"Graph factorization","score":0.4984288215637207},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4529035985469818},{"id":"https://openalex.org/keywords/graph-isomorphism","display_name":"Graph isomorphism","score":0.4240269362926483},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.10642564296722412},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.09773045778274536}],"concepts":[{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.8916818499565125},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.7238595485687256},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.7051172256469727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6877117156982422},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5286983251571655},{"id":"https://openalex.org/C176225458","wikidata":"https://www.wikidata.org/wiki/Q595971","display_name":"Graph database","level":3,"score":0.516293466091156},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5151978135108948},{"id":"https://openalex.org/C128115575","wikidata":"https://www.wikidata.org/wiki/Q5597083","display_name":"Graph factorization","level":5,"score":0.4984288215637207},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4529035985469818},{"id":"https://openalex.org/C61665672","wikidata":"https://www.wikidata.org/wiki/Q303100","display_name":"Graph isomorphism","level":4,"score":0.4240269362926483},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.10642564296722412},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.09773045778274536},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icdm.2003.1250974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.5.5389","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.5389","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.unc.edu/~weiwang/paper/ICDM03_2.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W4909282","https://openalex.org/W22405845","https://openalex.org/W1483679765","https://openalex.org/W1641749581","https://openalex.org/W2030766291","https://openalex.org/W2106441870","https://openalex.org/W2108014443","https://openalex.org/W2118349699","https://openalex.org/W2119148238","https://openalex.org/W2134356404","https://openalex.org/W2136593687","https://openalex.org/W2153301229","https://openalex.org/W2168924255","https://openalex.org/W2170726034","https://openalex.org/W4231101924","https://openalex.org/W6600927619","https://openalex.org/W6628973722","https://openalex.org/W6682515114","https://openalex.org/W6685146747"],"related_works":["https://openalex.org/W2393701947","https://openalex.org/W167435155","https://openalex.org/W1887488684","https://openalex.org/W2886672068","https://openalex.org/W84561889","https://openalex.org/W3008959778","https://openalex.org/W2750614246","https://openalex.org/W2604114816","https://openalex.org/W872425053","https://openalex.org/W3151217588"],"abstract_inverted_index":{"Frequent":[0],"subgraph":[1,46,72,118],"mining":[2,11,73,119],"is":[3,15,38],"an":[4,83],"active":[5],"research":[6],"topic":[7],"in":[8,26],"the":[9,54,92,115],"data":[10,21],"community.":[12],"A":[13],"graph":[14,36,41,85],"a":[16,69,78,110],"general":[17],"model":[18],"to":[19,90],"represent":[20],"and":[22,31,60,103],"has":[23],"been":[24,64],"used":[25],"many":[27],"domains":[28],"like":[29],"cheminformatics":[30],"bioinformatics.":[32],"Mining":[33],"patterns":[34],"from":[35],"databases":[37],"challenging":[39],"since":[40],"related":[42],"operations,":[43],"such":[44],"as":[45],"testing,":[47],"generally":[48],"have":[49,63,88],"higher":[50],"time":[51],"complexity":[52],"than":[53],"corresponding":[55],"operations":[56],"on":[57,101],"itemsets,":[58],"sequences,":[59],"trees,":[61],"which":[62,76],"studied":[65],"extensively.":[66],"We":[67],"propose":[68],"novel":[70],"frequent":[71],"algorithm:":[74],"FFSM,":[75],"employs":[77],"vertical":[79],"search":[80],"scheme":[81],"within":[82],"algebraic":[84],"framework":[86],"we":[87],"developed":[89],"reduce":[91],"number":[93],"of":[94],"redundant":[95],"candidates":[96],"proposed.":[97],"Our":[98],"empirical":[99],"study":[100],"synthetic":[102],"real":[104],"datasets":[105],"demonstrates":[106],"that":[107],"FFSM":[108],"achieves":[109],"substantial":[111],"performance":[112],"gain":[113],"over":[114],"current":[116],"start-of-the-art":[117],"algorithm":[120],"gSpan.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":24},{"year":2018,"cited_by_count":35},{"year":2017,"cited_by_count":32},{"year":2016,"cited_by_count":27},{"year":2015,"cited_by_count":38},{"year":2014,"cited_by_count":43},{"year":2013,"cited_by_count":37},{"year":2012,"cited_by_count":48}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}