{"id":"https://openalex.org/W1501856433","doi":"https://doi.org/10.1109/ijcnn.2005.1555942","title":"A new model for learning in graph domains","display_name":"A new model for learning in graph domains","publication_year":2006,"publication_date":"2006-01-05","ids":{"openalex":"https://openalex.org/W1501856433","doi":"https://doi.org/10.1109/ijcnn.2005.1555942","mag":"1501856433"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2005.1555942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555942","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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/A5022658803","display_name":"Marco Gori","orcid":"https://orcid.org/0000-0001-6337-5430"},"institutions":[{"id":"https://openalex.org/I102064193","display_name":"University of Siena","ror":"https://ror.org/01tevnk56","country_code":"IT","type":"education","lineage":["https://openalex.org/I102064193"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"M. Gori","raw_affiliation_strings":["Dipartimento di Ingegneria dell Informazione, Universit\u00e0 di Siena, Italy","Dipartirnento di Ingegneria dell'Informazione, Siena Univ., Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell Informazione, Universit\u00e0 di Siena, Italy","institution_ids":["https://openalex.org/I102064193"]},{"raw_affiliation_string":"Dipartirnento di Ingegneria dell'Informazione, Siena Univ., Italy","institution_ids":["https://openalex.org/I102064193"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039902490","display_name":"Gabriele Monfardini","orcid":null},"institutions":[{"id":"https://openalex.org/I102064193","display_name":"University of Siena","ror":"https://ror.org/01tevnk56","country_code":"IT","type":"education","lineage":["https://openalex.org/I102064193"]},{"id":"https://openalex.org/I4210101866","display_name":"Informa (Italy)","ror":"https://ror.org/017c2y429","country_code":"IT","type":"company","lineage":["https://openalex.org/I4210101866","https://openalex.org/I4210154378"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"G. Monfardini","raw_affiliation_strings":["Dipartimento di Ingegneria dell Informazione dell' Informazione, Universit\u00e0 di Siena, Italy","Dipartirnento di Ingegneria dell'Informazione, Siena Univ., Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell Informazione dell' Informazione, Universit\u00e0 di Siena, Italy","institution_ids":["https://openalex.org/I102064193","https://openalex.org/I4210101866"]},{"raw_affiliation_string":"Dipartirnento di Ingegneria dell'Informazione, Siena Univ., Italy","institution_ids":["https://openalex.org/I102064193"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020560480","display_name":"Franco Scarselli","orcid":"https://orcid.org/0000-0003-1307-0772"},"institutions":[{"id":"https://openalex.org/I102064193","display_name":"University of Siena","ror":"https://ror.org/01tevnk56","country_code":"IT","type":"education","lineage":["https://openalex.org/I102064193"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"F. Scarselli","raw_affiliation_strings":["Dipartimento di Ingegneria dell Informazione, Universit\u00e0 di Siena, Italy","Dipartirnento di Ingegneria dell'Informazione, Siena Univ., Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell Informazione, Universit\u00e0 di Siena, Italy","institution_ids":["https://openalex.org/I102064193"]},{"raw_affiliation_string":"Dipartirnento di Ingegneria dell'Informazione, Siena Univ., Italy","institution_ids":["https://openalex.org/I102064193"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9213,"has_fulltext":false,"cited_by_count":1936,"citation_normalized_percentile":{"value":0.94336324,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"2","issue":null,"first_page":"729","last_page":"734"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9855999946594238,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9706000089645386,"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/computer-science","display_name":"Computer science","score":0.7164327502250671},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6957970857620239},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5281904935836792},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5209609270095825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4685410261154175},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46164411306381226},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.43208983540534973},{"id":"https://openalex.org/keywords/undirected-graph","display_name":"Undirected graph","score":0.4315624237060547},{"id":"https://openalex.org/keywords/modular-decomposition","display_name":"Modular decomposition","score":0.4288368821144104},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4201255738735199},{"id":"https://openalex.org/keywords/indifference-graph","display_name":"Indifference graph","score":0.4113616347312927},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3787817358970642},{"id":"https://openalex.org/keywords/pathwidth","display_name":"Pathwidth","score":0.279704749584198},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.1275959014892578}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7164327502250671},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6957970857620239},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5281904935836792},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5209609270095825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4685410261154175},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46164411306381226},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.43208983540534973},{"id":"https://openalex.org/C3018234147","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Undirected graph","level":3,"score":0.4315624237060547},{"id":"https://openalex.org/C187407849","wikidata":"https://www.wikidata.org/wiki/Q6889712","display_name":"Modular decomposition","level":5,"score":0.4288368821144104},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4201255738735199},{"id":"https://openalex.org/C74133993","wikidata":"https://www.wikidata.org/wiki/Q3115472","display_name":"Indifference graph","level":3,"score":0.4113616347312927},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3787817358970642},{"id":"https://openalex.org/C43517604","wikidata":"https://www.wikidata.org/wiki/Q7144893","display_name":"Pathwidth","level":4,"score":0.279704749584198},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.1275959014892578},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2005.1555942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555942","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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. 2005 IEEE International Joint Conference on Neural Networks, 2005.","raw_type":"proceedings-article"},{"id":"pmh:oai:usiena-air.unisi.it:11365/19137","is_oa":false,"landing_page_url":"http://hdl.handle.net/11365/19137","pdf_url":null,"source":{"id":"https://openalex.org/S4377196319","display_name":"Use Siena air (University of Siena)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102064193","host_organization_name":"University of Siena","host_organization_lineage":["https://openalex.org/I102064193"],"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/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1566941664","https://openalex.org/W1573985123","https://openalex.org/W1597757028","https://openalex.org/W1607726853","https://openalex.org/W1881179843","https://openalex.org/W2007431958","https://openalex.org/W2127827747","https://openalex.org/W2140778946","https://openalex.org/W2166681504","https://openalex.org/W2478302134","https://openalex.org/W2756229660","https://openalex.org/W6639475024","https://openalex.org/W6744392878"],"related_works":["https://openalex.org/W1525720191","https://openalex.org/W80430187","https://openalex.org/W3002087433","https://openalex.org/W4387928694","https://openalex.org/W2358733572","https://openalex.org/W2031276298","https://openalex.org/W2008160316","https://openalex.org/W4288294436","https://openalex.org/W2955095032","https://openalex.org/W1892973443"],"abstract_inverted_index":{"In":[0],"several":[1],"applications":[2],"the":[3,23,42,49,81,108,111],"information":[4,37],"is":[5,99],"naturally":[6],"represented":[7],"by":[8],"graphs.":[9,68,93],"Traditional":[10],"approaches":[11],"cope":[12],"with":[13],"graphical":[14],"data":[15],"structures":[16],"using":[17],"a":[18,26,55],"preprocessing":[19,50],"phase":[20],"which":[21,106],"transforms":[22],"graphs":[24],"into":[25],"set":[27],"of":[28,65,80,85,110],"flat":[29],"vectors.":[30],"However,":[31],"in":[32],"this":[33],"way,":[34],"important":[35],"topological":[36],"may":[38,45],"be":[39,76],"lost":[40],"and":[41,74,91,101],"achieved":[43],"results":[44],"heavily":[46],"depend":[47],"on":[48,78],"stage.":[51],"This":[52],"paper":[53],"presents":[54],"new":[56],"neural":[57,61,72],"model,":[58],"called":[59],"graph":[60],"network":[62],"(GNN),":[63],"capable":[64],"directly":[66],"processing":[67],"GNNs":[69,98],"extends":[70],"recursive":[71],"networks":[73],"can":[75],"applied":[77],"most":[79],"practically":[82],"useful":[83],"kinds":[84],"graphs,":[86],"including":[87],"directed,":[88],"undirected,":[89],"labelled":[90],"cyclic":[92],"A":[94],"learning":[95],"algorithm":[96],"for":[97],"proposed":[100],"some":[102],"experiments":[103],"are":[104],"discussed":[105],"assess":[107],"properties":[109],"model.":[112]},"counts_by_year":[{"year":2026,"cited_by_count":91},{"year":2025,"cited_by_count":200},{"year":2024,"cited_by_count":268},{"year":2023,"cited_by_count":248},{"year":2022,"cited_by_count":220},{"year":2021,"cited_by_count":361},{"year":2020,"cited_by_count":285},{"year":2019,"cited_by_count":152},{"year":2018,"cited_by_count":64},{"year":2017,"cited_by_count":20},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":5}],"updated_date":"2026-08-14T07:06:38.338062","created_date":"2025-10-10T00:00:00"}
