{"id":"https://openalex.org/W2257693673","doi":"https://doi.org/10.1109/tnnls.2017.2705694","title":"Tree-Based Kernel for Graphs With Continuous Attributes","display_name":"Tree-Based Kernel for Graphs With Continuous Attributes","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2257693673","doi":"https://doi.org/10.1109/tnnls.2017.2705694","mag":"2257693673","pmid":"https://pubmed.ncbi.nlm.nih.gov/28622677"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2017.2705694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2705694","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1509.01116","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033850423","display_name":"Giovanni Da San Martino","orcid":"https://orcid.org/0000-0002-2609-483X"},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Giovanni Da San Martino","raw_affiliation_strings":["ALT Research Group, Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ALT Research Group, Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088959189","display_name":"Nicol\u00f2 Navarin","orcid":"https://orcid.org/0000-0002-4108-1754"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicolo Navarin","raw_affiliation_strings":["Department of Mathematics, University of Padua, Padova, Italy"],"raw_orcid":"https://orcid.org/0000-0002-4108-1754","affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Padua, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064873591","display_name":"Alessandro Sperduti","orcid":"https://orcid.org/0000-0002-8686-850X"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessandro Sperduti","raw_affiliation_strings":["Department of Mathematics, University of Padua, Padova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Padua, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9907,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.92868637,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"29","issue":"7","first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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":0.9998000264167786,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9955000281333923,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9945999979972839,"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":0.7200850248336792},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6914243102073669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5925312042236328},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5488609671592712},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5403412580490112},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.5369591116905212},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.507649302482605},{"id":"https://openalex.org/keywords/tree-kernel","display_name":"Tree kernel","score":0.48969200253486633},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4705736041069031},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4672733545303345},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.4660663902759552},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.45676377415657043},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.44472184777259827},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4318651854991913},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3937489986419678},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2736157178878784},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.17781201004981995},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.1726798415184021},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.10940679907798767}],"concepts":[{"id":"https://openalex.org/C100595998","wikidata":"https://www.wikidata.org/wiki/Q11731931","display_name":"Graph kernel","level":5,"score":0.7200850248336792},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6914243102073669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5925312042236328},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5488609671592712},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5403412580490112},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.5369591116905212},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.507649302482605},{"id":"https://openalex.org/C140417398","wikidata":"https://www.wikidata.org/wiki/Q16933942","display_name":"Tree kernel","level":5,"score":0.48969200253486633},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4705736041069031},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4672733545303345},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.4660663902759552},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.45676377415657043},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.44472184777259827},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4318651854991913},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3937489986419678},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2736157178878784},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.17781201004981995},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.1726798415184021},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.10940679907798767},{"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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tnnls.2017.2705694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2705694","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:28622677","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28622677","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:arXiv.org:1509.01116","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1509.01116","pdf_url":"https://arxiv.org/pdf/1509.01116","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:www.research.unipd.it:11577/3259918","is_oa":false,"landing_page_url":"http://hdl.handle.net/11577/3259918","pdf_url":null,"source":{"id":"https://openalex.org/S4377196283","display_name":"Research Padua  Archive (University of Padua)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1509.01116","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1509.01116","pdf_url":"https://arxiv.org/pdf/1509.01116","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321966","display_name":"Universit\u00e0 degli Studi di Padova","ror":"https://ror.org/00240q980"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W224064951","https://openalex.org/W608314793","https://openalex.org/W1179283095","https://openalex.org/W1482568066","https://openalex.org/W1816257748","https://openalex.org/W1984630281","https://openalex.org/W2026625220","https://openalex.org/W2092750499","https://openalex.org/W2099438806","https://openalex.org/W2107410045","https://openalex.org/W2112545207","https://openalex.org/W2123395972","https://openalex.org/W2124225821","https://openalex.org/W2124824205","https://openalex.org/W2137476097","https://openalex.org/W2144000913","https://openalex.org/W2147286743","https://openalex.org/W2185303849","https://openalex.org/W2232548815","https://openalex.org/W2245793494","https://openalex.org/W2280799770","https://openalex.org/W2407839853","https://openalex.org/W2607582373","https://openalex.org/W4245055982","https://openalex.org/W6608848962","https://openalex.org/W6628717828","https://openalex.org/W6676388157","https://openalex.org/W6678167290","https://openalex.org/W6678945949","https://openalex.org/W6679209274","https://openalex.org/W6680132778","https://openalex.org/W6695479203"],"related_works":["https://openalex.org/W3013206934","https://openalex.org/W3100948281","https://openalex.org/W1983263273","https://openalex.org/W4311138679","https://openalex.org/W2090782076","https://openalex.org/W3081470858","https://openalex.org/W1590832708","https://openalex.org/W2179275589","https://openalex.org/W2883617201","https://openalex.org/W2096302783"],"abstract_inverted_index":{"The":[0,92],"availability":[1],"of":[2,100,117,144,163],"graph":[3,74,90],"data":[4,131],"with":[5,27],"node":[6,31,39],"attributes":[7,40],"that":[8,58,134],"can":[9],"be":[10],"either":[11],"discrete":[12,30],"or":[13,37],"real-valued":[14],"is":[15,137],"constantly":[16],"increasing.":[17],"While":[18],"existing":[19],"Kernel":[20],"methods":[21],"are":[22,84],"effective":[23],"techniques":[24],"for":[25,45,54,62,76],"dealing":[26],"graphs":[28],"having":[29],"labels,":[32],"their":[33],"adaptation":[34],"to":[35,95,156],"nondiscrete":[36],"continuous":[38,79],"has":[41],"been":[42,66],"limited,":[43],"mainly":[44],"computational":[46,63],"issues.":[47],"Recently,":[48],"a":[49,73,107],"few":[50],"kernels":[51,103,160],"especially":[52],"tailored":[53],"this":[55,69],"domain,":[56],"and":[57,78],"trade":[59],"predictive":[60],"performance":[61],"efficiency,":[64],"have":[65],"proposed.":[67],"In":[68],"brief,":[70],"we":[71],"propose":[72],"kernel":[75,93,136],"complex":[77],"nodes'":[80],"attributes,":[81],"whose":[82],"features":[83],"tree":[85],"structures":[86],"extracted":[87],"from":[88],"specific":[89],"visits.":[91],"manages":[94],"keep":[96],"the":[97,101,118,135,138,150,157,169],"same":[98],"complexity":[99,123],"state-of-the-art":[102,159],"while":[104,166],"implicitly":[105],"using":[106],"larger":[108],"feature":[109],"space.":[110],"We":[111],"further":[112],"present":[113],"an":[114],"approximated":[115,151],"variant":[116],"kernel,":[119],"which":[120],"reduces":[121],"its":[122],"significantly.":[124],"Experimental":[125],"results":[126],"obtained":[127],"on":[128,142],"six":[129],"real-world":[130],"sets":[132],"show":[133],"best":[139],"performing":[140],"one":[141],"most":[143,148],"them.":[145],"Moreover,":[146],"in":[147,161],"cases,":[149],"version":[152],"reaches":[153],"comparable":[154],"performances":[155],"current":[158],"terms":[162],"classification":[164],"accuracy":[165],"greatly":[167],"shortening":[168],"running":[170],"times.":[171]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
