{"id":"https://openalex.org/W4229586722","doi":"https://doi.org/10.1109/icpr.2004.1334546","title":"Structural graph matching with polynomial bounds on memory and on worst-case effort","display_name":"Structural graph matching with polynomial bounds on memory and on worst-case effort","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W4229586722","doi":"https://doi.org/10.1109/icpr.2004.1334546"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2004.1334546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2004.1334546","pdf_url":null,"source":{"id":"https://openalex.org/S4363608750","display_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","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":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","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/A5068375475","display_name":"F.W. DePiero","orcid":null},"institutions":[{"id":"https://openalex.org/I149919469","display_name":"California Polytechnic State University","ror":"https://ror.org/001gpfp45","country_code":"US","type":"education","lineage":["https://openalex.org/I149919469"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"F.W. DePiero","raw_affiliation_strings":["CalPoly State Univ., San Luis Obispo, CA, USA","CalPoly State University, San Louis Obispo, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CalPoly State Univ., San Luis Obispo, CA, USA","institution_ids":["https://openalex.org/I149919469"]},{"raw_affiliation_string":"CalPoly State University, San Louis Obispo, CA, USA","institution_ids":["https://openalex.org/I149919469"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5068375475"],"corresponding_institution_ids":["https://openalex.org/I149919469"],"apc_list":null,"apc_paid":null,"fwci":0.2376,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49475825,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"stan cs 73 349","issue":null,"first_page":"379","last_page":"382 Vol.3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":1.0,"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":0.9965999722480774,"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/T11106","display_name":"Data Management and Algorithms","score":0.9925000071525574,"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/matching","display_name":"Matching (statistics)","score":0.6117528676986694},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6063500642776489},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.520837128162384},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4902932941913605},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46991056203842163},{"id":"https://openalex.org/keywords/graph-factorization","display_name":"Graph factorization","score":0.46905234456062317},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4534086287021637},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.44841259717941284},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.4482533931732178},{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.43646183609962463},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43633633852005005},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.39864304661750793},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3789904713630676},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3137695789337158},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.15894359350204468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.152822345495224},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.07763609290122986}],"concepts":[{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6117528676986694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6063500642776489},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.520837128162384},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4902932941913605},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46991056203842163},{"id":"https://openalex.org/C128115575","wikidata":"https://www.wikidata.org/wiki/Q5597083","display_name":"Graph factorization","level":5,"score":0.46905234456062317},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4534086287021637},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.44841259717941284},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4482533931732178},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.43646183609962463},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43633633852005005},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.39864304661750793},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3789904713630676},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3137695789337158},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.15894359350204468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.152822345495224},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.07763609290122986},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2004.1334546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2004.1334546","pdf_url":null,"source":{"id":"https://openalex.org/S4363608750","display_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","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":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","raw_type":"proceedings-article"},{"id":"pmh:oai:digitalcommons.calpoly.edu:eeng_fac-1013","is_oa":false,"landing_page_url":"https://digitalcommons.calpoly.edu/eeng_fac/14","pdf_url":null,"source":{"id":"https://openalex.org/S4377196328","display_name":"DigitalCommons - CalPoly (California State Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98947143","host_organization_name":"California State Polytechnic University","host_organization_lineage":["https://openalex.org/I98947143"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electrical Engineering","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1600475114","https://openalex.org/W1974854605","https://openalex.org/W2009757396","https://openalex.org/W2010541316","https://openalex.org/W2029059958","https://openalex.org/W2073067110","https://openalex.org/W2092463494","https://openalex.org/W2098109165","https://openalex.org/W2115139257","https://openalex.org/W2122929441","https://openalex.org/W2145098817","https://openalex.org/W2148116692","https://openalex.org/W2152132697","https://openalex.org/W2159537329","https://openalex.org/W2165835775","https://openalex.org/W6682481259"],"related_works":["https://openalex.org/W2393701947","https://openalex.org/W1512756268","https://openalex.org/W2542507283","https://openalex.org/W2532922352","https://openalex.org/W2886672068","https://openalex.org/W167435155","https://openalex.org/W2035609387","https://openalex.org/W2953496651","https://openalex.org/W1887488684","https://openalex.org/W2604114816"],"abstract_inverted_index":{"A":[0],"new":[1],"method":[2,14,22],"of":[3,42,91],"structural":[4,69],"graph":[5],"matching":[6],"is":[7,23,65],"introduced":[8],"and":[9,15,31,44],"compared":[10],"against":[11,16],"an":[12],"existing":[13],"the":[17,33,60,62,92],"maximum":[18,93],"common":[19,63,94],"subgraph.":[20,95],"The":[21],"approximate":[24],"with":[25,46,77,102],"polynomial":[26],"bounds":[27],"on":[28,32,39,68],"both":[29],"memory":[30],"worst-case":[34],"compute":[35],"effort.":[36],"Methods":[37],"work":[38],"arbitrary":[40],"types":[41],"graphs":[43,49,103],"tests":[45],"strongly":[47],"regular":[48],"are":[50,57,75,83,100],"included.":[51],"No":[52],"node":[53],"or":[54],"edge":[55],"colors":[56],"needed":[58],"in":[59],"methods;":[61],"subgraph":[64],"extracted":[66],"based":[67],"comparisons":[70],"only.":[71],"Monte":[72],"Carlo":[73],"trials":[74,99],"benchmarked":[76],"100%":[78],"additional":[79],"(clutter)":[80],"nodes.":[81,107],"Results":[82],"shown":[84],"to":[85,105],"be":[86],"typically":[87],"within":[88],"1-2":[89],"nodes":[90],"Over":[96],"7500":[97],"test":[98],"reported":[101],"up":[104],"100":[106]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
