{"id":"https://openalex.org/W2112688370","doi":"https://doi.org/10.1145/2339530.2339614","title":"A structural cluster kernel for learning on graphs","display_name":"A structural cluster kernel for learning on graphs","publication_year":2012,"publication_date":"2012-08-12","ids":{"openalex":"https://openalex.org/W2112688370","doi":"https://doi.org/10.1145/2339530.2339614","mag":"2112688370"},"language":"en","primary_location":{"id":"doi:10.1145/2339530.2339614","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2339530.2339614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5056807104","display_name":"Madeleine Seeland","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Madeleine Seeland","raw_affiliation_strings":["Technische Universit\u00e4t M\u00fcnchen, Garching bei M\u00fcnchen, Germany","Technische Universitat Munchen, Garching bei Munchen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t M\u00fcnchen, Garching bei M\u00fcnchen, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Technische Universitat Munchen, Garching bei Munchen, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026210150","display_name":"Andreas Karwath","orcid":"https://orcid.org/0000-0002-6942-3760"},"institutions":[{"id":"https://openalex.org/I197323543","display_name":"Johannes Gutenberg University Mainz","ror":"https://ror.org/023b0x485","country_code":"DE","type":"education","lineage":["https://openalex.org/I197323543"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Karwath","raw_affiliation_strings":["Johannes Gutenberg-Universit\u00e4t Mainz, Mainz, Germany","Johannes Gutenberg Universitat Mainz, Mainz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johannes Gutenberg-Universit\u00e4t Mainz, Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]},{"raw_affiliation_string":"Johannes Gutenberg Universitat Mainz, Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102744434","display_name":"Stefan Kr\u00e4mer","orcid":"https://orcid.org/0000-0003-0136-2540"},"institutions":[{"id":"https://openalex.org/I197323543","display_name":"Johannes Gutenberg University Mainz","ror":"https://ror.org/023b0x485","country_code":"DE","type":"education","lineage":["https://openalex.org/I197323543"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Kramer","raw_affiliation_strings":["Johannes Gutenberg-Universit\u00e4t Mainz, Mainz, Germany","Johannes Gutenberg Universitat Mainz, Mainz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johannes Gutenberg-Universit\u00e4t Mainz, Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]},{"raw_affiliation_string":"Johannes Gutenberg Universitat Mainz, Mainz, Germany","institution_ids":["https://openalex.org/I197323543"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"516","last_page":"524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.986299991607666,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.97079998254776,"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/graph-kernel","display_name":"Graph kernel","score":0.8099003434181213},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6696650981903076},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.650056004524231},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6189126968383789},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.529954731464386},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5102529525756836},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5080127716064453},{"id":"https://openalex.org/keywords/string-kernel","display_name":"String kernel","score":0.48503512144088745},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47153550386428833},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4664928913116455},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.45968741178512573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.421942800283432},{"id":"https://openalex.org/keywords/tree-kernel","display_name":"Tree kernel","score":0.4129016399383545},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4002804160118103},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38058561086654663},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2478780746459961},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.16449585556983948},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1418137550354004}],"concepts":[{"id":"https://openalex.org/C100595998","wikidata":"https://www.wikidata.org/wiki/Q11731931","display_name":"Graph kernel","level":5,"score":0.8099003434181213},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6696650981903076},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.650056004524231},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6189126968383789},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.529954731464386},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5102529525756836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5080127716064453},{"id":"https://openalex.org/C55851704","wikidata":"https://www.wikidata.org/wiki/Q7623983","display_name":"String kernel","level":5,"score":0.48503512144088745},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47153550386428833},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4664928913116455},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.45968741178512573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.421942800283432},{"id":"https://openalex.org/C140417398","wikidata":"https://www.wikidata.org/wiki/Q16933942","display_name":"Tree kernel","level":5,"score":0.4129016399383545},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4002804160118103},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38058561086654663},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2478780746459961},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.16449585556983948},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1418137550354004},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2339530.2339614","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2339530.2339614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/61c18d22-fbb9-462d-8f51-6c00580028f9","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/61c18d22-fbb9-462d-8f51-6c00580028f9","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Seeland, M, Karwath, A & Kramer, S 2012, 'A structural cluster kernel for learning on graphs', pp. 516-524. https://doi.org/10.1145/2339530.2339614","raw_type":"conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W87060577","https://openalex.org/W1500548371","https://openalex.org/W1533958480","https://openalex.org/W1545890730","https://openalex.org/W1560868107","https://openalex.org/W1861597095","https://openalex.org/W1992332072","https://openalex.org/W2017091502","https://openalex.org/W2032245355","https://openalex.org/W2040324575","https://openalex.org/W2073993379","https://openalex.org/W2111952849","https://openalex.org/W2113592823","https://openalex.org/W2114318860","https://openalex.org/W2120199131","https://openalex.org/W2129893339","https://openalex.org/W2131626361","https://openalex.org/W2136490963","https://openalex.org/W2137476097","https://openalex.org/W2153037537","https://openalex.org/W2167187529","https://openalex.org/W2170726034","https://openalex.org/W2215622313","https://openalex.org/W2341476366","https://openalex.org/W2911738047","https://openalex.org/W2973321334","https://openalex.org/W3123294050","https://openalex.org/W6632683325","https://openalex.org/W6676772307"],"related_works":["https://openalex.org/W3013206934","https://openalex.org/W2130792056","https://openalex.org/W3099811568","https://openalex.org/W1535136526","https://openalex.org/W1590832708","https://openalex.org/W2090782076","https://openalex.org/W1983263273","https://openalex.org/W3081470858","https://openalex.org/W2147750455","https://openalex.org/W32136235"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"graph":[3,57,68],"kernels":[4],"have":[5],"received":[6],"considerable":[7],"interest":[8],"within":[9],"the":[10,32,36,65,76,79,85],"machine":[11],"learning":[12],"and":[13,103,109],"data":[14],"mining":[15],"community.":[16],"Here,":[17],"we":[18],"introduce":[19],"a":[20,50,101,104,113],"novel":[21,41,98],"approach":[22,60],"enabling":[23],"kernel":[24,44,99],"methods":[25],"to":[26,54,91,107],"utilize":[27],"additional":[28],"information":[29],"hidden":[30],"in":[31,100],"structural":[33,42,51,93],"neighborhood":[34],"of":[35,115,118],"graphs":[37,80],"under":[38],"consideration.":[39],"Our":[40],"cluster":[43],"(SCK)":[45],"incorporates":[46],"similarities":[47],"induced":[48],"by":[49,75,84],"clustering":[52],"algorithm":[53],"improve":[55],"state-of-the-art":[56],"kernels.":[58],"The":[59],"taken":[61],"is":[62],"based":[63],"on":[64,112],"idea":[66],"that":[67],"similarity":[69,77,86],"can":[70],"not":[71],"only":[72],"be":[73],"described":[74],"between":[78],"themselves,":[81],"but":[82],"also":[83],"they":[87],"possess":[88],"with":[89],"respect":[90],"their":[92],"neighborhood.":[94],"We":[95],"applied":[96],"our":[97],"supervised":[102],"semi-supervised":[105],"setting":[106],"regression":[108],"classification":[110],"problems":[111],"number":[114],"real-world":[116],"datasets":[117],"molecular":[119],"graphs.":[120]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
