{"id":"https://openalex.org/W2899525346","doi":"https://doi.org/10.1109/icassp.2019.8682836","title":"A Recurrent Graph Neural Network for Multi-relational Data","display_name":"A Recurrent Graph Neural Network for Multi-relational Data","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2899525346","doi":"https://doi.org/10.1109/icassp.2019.8682836","mag":"2899525346"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1811.02061","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023028617","display_name":"Vassilis N. Ioannidis","orcid":"https://orcid.org/0000-0002-8367-0733"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vassilis N. Ioannidis","raw_affiliation_strings":["Digital Technology Center and Dept. of ECE, University of Minnesota, Minneapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Digital Technology Center and Dept. of ECE, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054312245","display_name":"Antonio G. Marqu\u00e9s","orcid":"https://orcid.org/0000-0002-4642-7718"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio G. Marques","raw_affiliation_strings":["Dept. of Signal Theory and Comms, King Juan Carlos University, Madrid, Spain","Dept. of Signal Theory and Comms., King Juan Carlos University, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Signal Theory and Comms, King Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Dept. of Signal Theory and Comms., King Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026758314","display_name":"Georgios B. Giannakis","orcid":"https://orcid.org/0000-0002-0196-0260"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Georgios B. Giannakis","raw_affiliation_strings":["Digital Technology Center and Dept. of ECE, University of Minnesota, Minneapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Digital Technology Center and Dept. of ECE, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8157","last_page":"8161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9909999966621399,"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":0.9873999953269958,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6959278583526611},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6666402816772461},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6329896450042725},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5615653991699219},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5462247729301453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5165085196495056},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47514867782592773},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42971962690353394},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34525877237319946}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6959278583526611},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6666402816772461},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6329896450042725},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5615653991699219},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5462247729301453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5165085196495056},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47514867782592773},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42971962690353394},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34525877237319946},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icassp.2019.8682836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1811.02061","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.02061","pdf_url":"https://arxiv.org/pdf/1811.02061","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.1811.02061","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1811.02061","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:2899525346","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1811.02061","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.02061","pdf_url":"https://arxiv.org/pdf/1811.02061","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2899525346.pdf","grobid_xml":"https://content.openalex.org/works/W2899525346.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W950821216","https://openalex.org/W1498436455","https://openalex.org/W1690143098","https://openalex.org/W2061901927","https://openalex.org/W2101491865","https://openalex.org/W2104290444","https://openalex.org/W2139823104","https://openalex.org/W2153959628","https://openalex.org/W2407712691","https://openalex.org/W2471801048","https://openalex.org/W2558748708","https://openalex.org/W2565330852","https://openalex.org/W2769897290","https://openalex.org/W2796189583","https://openalex.org/W2798598284","https://openalex.org/W2888816596","https://openalex.org/W2898091232","https://openalex.org/W2953384591","https://openalex.org/W2963312446","https://openalex.org/W2963674505","https://openalex.org/W2964015378","https://openalex.org/W2964121744","https://openalex.org/W2964321699","https://openalex.org/W3037826211","https://openalex.org/W3120740533","https://openalex.org/W6631190155","https://openalex.org/W6675747103","https://openalex.org/W6680434193","https://openalex.org/W6699364125","https://openalex.org/W6720006811","https://openalex.org/W6720275808","https://openalex.org/W6726873649","https://openalex.org/W6731918294","https://openalex.org/W6749968476"],"related_works":["https://openalex.org/W2889778976","https://openalex.org/W3037579346","https://openalex.org/W3163735432","https://openalex.org/W3126412650","https://openalex.org/W3129756592","https://openalex.org/W3006129586","https://openalex.org/W3025414823","https://openalex.org/W3041689858","https://openalex.org/W3121197195","https://openalex.org/W3097836457","https://openalex.org/W2994506732","https://openalex.org/W3128306840","https://openalex.org/W2808610674","https://openalex.org/W3174340586","https://openalex.org/W3145277743","https://openalex.org/W3016124664","https://openalex.org/W2794980531","https://openalex.org/W2011565604","https://openalex.org/W3041915817","https://openalex.org/W2605067594"],"abstract_inverted_index":{"The":[0],"era":[1],"of":[2,16,45,53,69,102,112],"\"data":[3],"deluge\"":[4],"has":[5],"sparked":[6],"the":[7,46,51,56,60,67,110,113,121,126],"interest":[8],"in":[9,13],"graph-based":[10,70],"learning":[11,39,86],"methods":[12],"a":[14,30,84],"number":[15],"disciplines":[17],"such":[18],"as":[19],"sociology,":[20],"biology,":[21],"neuroscience,":[22],"or":[23],"engineering.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28],"introduce":[29],"graph":[31],"recurrent":[32],"neural":[33],"network":[34],"(GRNN)":[35],"for":[36],"scalable":[37],"semi-supervised":[38],"from":[40],"multi-relational":[41,54],"data.":[42],"Key":[43],"aspects":[44],"novel":[47],"GRNN":[48],"architecture":[49,87],"are":[50],"use":[52],"graphs,":[55],"dynamic":[57],"adaptation":[58],"to":[59,72,82,109,130],"different":[61],"relations":[62],"via":[63],"learnable":[64],"weights,":[65],"and":[66,75,92,104,124],"consideration":[68],"regularizers":[71],"promote":[73],"smoothness":[74],"alleviate":[76],"over-parametrization.":[77],"Our":[78],"ultimate":[79],"goal":[80],"is":[81],"design":[83,122],"powerful":[85],"able":[88],"to:":[89],"discover":[90],"complex":[91],"highly":[93],"non-linear":[94],"data":[95],"associations,":[96],"combine":[97],"(and":[98],"select)":[99],"multiple":[100],"types":[101],"relations,":[103],"scale":[105],"gracefully":[106],"with":[107,117],"respect":[108],"size":[111],"graph.":[114],"Numerical":[115],"tests":[116],"real":[118],"datasets":[119],"corroborate":[120],"goals":[123],"illustrate":[125],"performance":[127],"gains":[128],"relative":[129],"competing":[131],"alternatives.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}