{"id":"https://openalex.org/W3209336272","doi":"https://doi.org/10.1145/3459637.3482067","title":"Boosting Graph Alignment Algorithms","display_name":"Boosting Graph Alignment Algorithms","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3209336272","doi":"https://doi.org/10.1145/3459637.3482067","mag":"3209336272"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482067","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://pure.au.dk/portal/en/publications/a6a8d28c-b44e-4466-86dc-57213330e2b9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039262091","display_name":"Alexander Kyster","orcid":"https://orcid.org/0000-0003-4823-4060"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Alexander Frederiksen Kyster","raw_affiliation_strings":["Aarhus University, Aarhus, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aarhus University, Aarhus, Denmark","institution_ids":["https://openalex.org/I204337017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024986736","display_name":"Simon Daugaard Nielsen","orcid":"https://orcid.org/0000-0002-5230-5231"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Simon Daugaard Nielsen","raw_affiliation_strings":["Aarhus University, Aarhus, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aarhus University, Aarhus, Denmark","institution_ids":["https://openalex.org/I204337017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008532692","display_name":"Judith Hermanns","orcid":"https://orcid.org/0000-0002-2170-4635"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Judith Hermanns","raw_affiliation_strings":["Aarhus University, Aarhus, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aarhus University, Aarhus, Denmark","institution_ids":["https://openalex.org/I204337017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009276458","display_name":"Davide Mottin","orcid":"https://orcid.org/0000-0001-8256-2258"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Davide Mottin","raw_affiliation_strings":["Aarhus University, Aarhus, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aarhus University, Aarhus, Denmark","institution_ids":["https://openalex.org/I204337017"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103092057","display_name":"Panagiotis Karras","orcid":"https://orcid.org/0000-0003-0509-9129"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Panagiotis Karras","raw_affiliation_strings":["Aarhus University, Aarhus, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aarhus University, Aarhus, Denmark","institution_ids":["https://openalex.org/I204337017"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204337017"],"apc_list":null,"apc_paid":null,"fwci":0.4396,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63228449,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3166","last_page":"3170"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991999864578247,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991999864578247,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9861000180244446,"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":0.7365610599517822},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.5711913704872131},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.5577161312103271},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5257540345191956},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5078485608100891},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5016956329345703},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.49942636489868164},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.4663825035095215},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.46432915329933167},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4424424171447754},{"id":"https://openalex.org/keywords/graph-algorithms","display_name":"Graph algorithms","score":0.41560444235801697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2103341817855835}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7365610599517822},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.5711913704872131},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.5577161312103271},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5257540345191956},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5078485608100891},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5016956329345703},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.49942636489868164},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.4663825035095215},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.46432915329933167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4424424171447754},{"id":"https://openalex.org/C2986651925","wikidata":"https://www.wikidata.org/wiki/Q1514868","display_name":"Graph algorithms","level":3,"score":0.41560444235801697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2103341817855835},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3459637.3482067","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire/a6a8d28c-b44e-4466-86dc-57213330e2b9","is_oa":true,"landing_page_url":"https://pure.au.dk/portal/en/publications/a6a8d28c-b44e-4466-86dc-57213330e2b9","pdf_url":null,"source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kyster, A F, Nielsen, S D, Hermanns, J, Mottin, D & Karras, P 2021, Boosting Graph Alignment Algorithms. in Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM '21). Association for Computing Machinery, New York, pp. 3166-3170, 30th ACM International Conference on Information and Knowledge Management, CIKM 2021, Virtual, Online, Australia, 01/11/2021. https://doi.org/10.1145/3459637.3482067","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:pure.atira.dk:publications/a6a8d28c-b44e-4466-86dc-57213330e2b9","is_oa":true,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85119170982&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306400063","display_name":"Scopus (Elsevier)","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kyster, A F, Nielsen, S D, Hermanns, J, Mottin, D & Karras, P 2021, Boosting Graph Alignment Algorithms. in Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM '21). Association for Computing Machinery, New York, pp. 3166-3170, 30th ACM International Conference on Information and Knowledge Management, CIKM 2021, Virtual, Online, Australia, 01/11/2021. https://doi.org/10.1145/3459637.3482067","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire/a6a8d28c-b44e-4466-86dc-57213330e2b9","is_oa":true,"landing_page_url":"https://pure.au.dk/portal/en/publications/a6a8d28c-b44e-4466-86dc-57213330e2b9","pdf_url":null,"source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kyster, A F, Nielsen, S D, Hermanns, J, Mottin, D & Karras, P 2021, Boosting Graph Alignment Algorithms. in Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM '21). Association for Computing Machinery, New York, pp. 3166-3170, 30th ACM International Conference on Information and Knowledge Management, CIKM 2021, Virtual, Online, Australia, 01/11/2021. https://doi.org/10.1145/3459637.3482067","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W131619556","https://openalex.org/W838060996","https://openalex.org/W1854214752","https://openalex.org/W1974682889","https://openalex.org/W1997421642","https://openalex.org/W2009536104","https://openalex.org/W2047161559","https://openalex.org/W2056124433","https://openalex.org/W2107427454","https://openalex.org/W2139688603","https://openalex.org/W2144116555","https://openalex.org/W2153929049","https://openalex.org/W2154851992","https://openalex.org/W2165558283","https://openalex.org/W2171108134","https://openalex.org/W2391555403","https://openalex.org/W2607500032","https://openalex.org/W2755088640","https://openalex.org/W2788614083","https://openalex.org/W2789134258","https://openalex.org/W2888657195","https://openalex.org/W2950627632","https://openalex.org/W2963701864","https://openalex.org/W2964024205","https://openalex.org/W3025159219","https://openalex.org/W3072176192","https://openalex.org/W3098702884","https://openalex.org/W3103148916","https://openalex.org/W3103296165","https://openalex.org/W3103995645","https://openalex.org/W3104097132","https://openalex.org/W3151791879","https://openalex.org/W3170097993","https://openalex.org/W4291474301"],"related_works":["https://openalex.org/W3206528106","https://openalex.org/W3036264823","https://openalex.org/W2912814903","https://openalex.org/W2123605750","https://openalex.org/W2088740331","https://openalex.org/W3038102983","https://openalex.org/W2950907416","https://openalex.org/W1559483280","https://openalex.org/W2082479932","https://openalex.org/W2932872266"],"abstract_inverted_index":{"The":[0],"problem":[1,20],"of":[2,13,79],"graph":[3,27,47,56,65],"alignment":[4,32,66,104],"is":[5],"to":[6,38,42,93],"find":[7],"corresponding":[8],"nodes":[9],"between":[10],"a":[11,22,85],"pair":[12],"graphs.":[14],"Past":[15],"work":[16],"has":[17],"treated":[18],"the":[19,26,31,40,103],"in":[21,77,102],"monolithic":[23],"fashion,":[24],"with":[25],"as":[28,33],"input":[29,46],"and":[30,72,74],"output,":[34],"offering":[35],"limited":[36],"opportunities":[37],"adapt":[39],"algorithm":[41,96],"task":[43],"requirements":[44],"or":[45],"characteristics.":[48],"Recently,":[49],"node":[50,69],"embedding":[51],"techniques":[52],"are":[53,99],"utilized":[54],"for":[55],"alignment.":[57],"In":[58,84],"this":[59,91],"paper,":[60],"we":[61,89],"study":[62],"two":[63],"state-of-the-art":[64],"algorithms":[67],"utilizing":[68],"representations,":[70],"CONE-Align":[71],"GRASP,":[73],"describe":[75],"them":[76],"terms":[78],"an":[80],"overarching":[81],"modular":[82],"framework.":[83],"targeted":[86],"experimental":[87],"study,":[88],"exploit":[90],"modularity":[92],"develop":[94],"enhanced":[95],"variants":[97],"that":[98],"more":[100],"effective":[101],"task.":[105]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
