{"id":"https://openalex.org/W3089885888","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207513","title":"Let the Margin SlidE<sup>\u00b1</sup>for Knowledge Graph Embeddings via a Correntropy Objective Function","display_name":"Let the Margin SlidE<sup>\u00b1</sup>for Knowledge Graph Embeddings via a Correntropy Objective Function","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3089885888","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207513","mag":"3089885888"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5043741534","display_name":"Mojtaba Nayyeri","orcid":"https://orcid.org/0000-0002-9177-0312"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Mojtaba Nayyeri","raw_affiliation_strings":["University of Bonn,SDA Research,Bonn,Germany","SDA Research, University of Bonn, Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn,SDA Research,Bonn,Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"SDA Research, University of Bonn, Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082718630","display_name":"Xiaotian Zhou","orcid":"https://orcid.org/0000-0002-3237-5347"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xiaotian Zhou","raw_affiliation_strings":["University of Bonn,SDA Research,Bonn,Germany","SDA Research, University of Bonn, Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn,SDA Research,Bonn,Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"SDA Research, University of Bonn, Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102785999","display_name":"Sahar Vahdati","orcid":"https://orcid.org/0000-0002-7171-169X"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sahar Vahdati","raw_affiliation_strings":["University of Oxford,Oxford,UK","University of Oxford, Oxford, UK"],"affiliations":[{"raw_affiliation_string":"University of Oxford,Oxford,UK","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"University of Oxford, Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034225342","display_name":"Reza Izanloo","orcid":null},"institutions":[{"id":"https://openalex.org/I86958956","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752","country_code":"IR","type":"education","lineage":["https://openalex.org/I86958956"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Reza Izanloo","raw_affiliation_strings":["Ferdowsi University of Mashhad,Mashhad,Iran","Ferdowsi University of Mashhad, Mashhad, Iran"],"affiliations":[{"raw_affiliation_string":"Ferdowsi University of Mashhad,Mashhad,Iran","institution_ids":["https://openalex.org/I86958956"]},{"raw_affiliation_string":"Ferdowsi University of Mashhad, Mashhad, Iran","institution_ids":["https://openalex.org/I86958956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054409762","display_name":"Hamed Shariat Yazdi","orcid":null},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hamed Shariat Yazdi","raw_affiliation_strings":["University of Bonn,SDA Research,Bonn,Germany","SDA Research, University of Bonn, Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn,SDA Research,Bonn,Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"SDA Research, University of Bonn, Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067133778","display_name":"Jens Lehmann","orcid":"https://orcid.org/0000-0001-9108-4278"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jens Lehmann","raw_affiliation_strings":["University of Bonn Fraunhofer IAIS,SDA Research,Bonn,Germany","SDA Research, University of Bonn Fraunhofer IAIS, Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn Fraunhofer IAIS,SDA Research,Bonn,Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"SDA Research, University of Bonn Fraunhofer IAIS, Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5043741534"],"corresponding_institution_ids":["https://openalex.org/I135140700"],"apc_list":null,"apc_paid":null,"fwci":0.5493,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73174942,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"4","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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":1.0,"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/T10028","display_name":"Topic Modeling","score":0.9991000294685364,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9821000099182129,"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/margin","display_name":"Margin (machine learning)","score":0.7114406824111938},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.698689341545105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6613607406616211},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5038389563560486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4942462742328644},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45068541169166565},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4136899411678314},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.41317513585090637},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3786473274230957},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37800875306129456},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37576597929000854}],"concepts":[{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7114406824111938},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.698689341545105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6613607406616211},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5038389563560486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4942462742328644},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45068541169166565},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4136899411678314},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.41317513585090637},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3786473274230957},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37800875306129456},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37576597929000854},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-614603","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-614603.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IAIS","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/409470","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/409470","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"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":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1512387364","https://openalex.org/W1552847225","https://openalex.org/W1596986901","https://openalex.org/W1894439495","https://openalex.org/W2057047055","https://openalex.org/W2080133951","https://openalex.org/W2081580037","https://openalex.org/W2094728533","https://openalex.org/W2099752825","https://openalex.org/W2101802482","https://openalex.org/W2127795553","https://openalex.org/W2135160607","https://openalex.org/W2163073637","https://openalex.org/W2178228255","https://openalex.org/W2184957013","https://openalex.org/W2247119764","https://openalex.org/W2250342289","https://openalex.org/W2283196293","https://openalex.org/W2296319761","https://openalex.org/W2509893387","https://openalex.org/W2515462165","https://openalex.org/W2532938041","https://openalex.org/W2563010554","https://openalex.org/W2768012150","https://openalex.org/W2797763839","https://openalex.org/W2909137510","https://openalex.org/W2940576506","https://openalex.org/W2944192631","https://openalex.org/W2949434543","https://openalex.org/W2963432357","https://openalex.org/W2963450615","https://openalex.org/W4250589301","https://openalex.org/W4288364205","https://openalex.org/W6635815790","https://openalex.org/W6675255137","https://openalex.org/W6678830454","https://openalex.org/W6683461794","https://openalex.org/W6728592800","https://openalex.org/W6751747387","https://openalex.org/W6758075616","https://openalex.org/W6761665218"],"related_works":["https://openalex.org/W2900382651","https://openalex.org/W1981879262","https://openalex.org/W2363417484","https://openalex.org/W4225863708","https://openalex.org/W1599970036","https://openalex.org/W1480103567","https://openalex.org/W158852162","https://openalex.org/W2003651848","https://openalex.org/W1849827364","https://openalex.org/W2119384858"],"abstract_inverted_index":{"Embedding":[0,31,53,229],"models":[1,32,54],"based":[2],"on":[3,57,207,239],"translation":[4],"and":[5,47,77,95,99,216,233],"rotation":[6],"have":[7,23,110],"gained":[8],"significant":[9],"attention":[10],"in":[11,33,66],"link":[12,40,240],"prediction":[13,41,241],"tasks":[14],"for":[15,106,130,225],"knowledge":[16],"graphs.":[17],"Most":[18],"of":[19,28,39,51,62,97,117,132,137,168,183,196,210,220],"the":[20,25,37,49,58,63,81,93,102,111,115,118,133,135,150,158,178,184,194,197,218],"earlier":[21],"works":[22],"modified":[24],"score":[26],"function":[27],"Knowledge":[29,227],"Graph":[30,228],"order":[34],"to":[35,71,121,144,148,154,176,192,200],"improve":[36],"performance":[38,50],"tasks.":[42,242],"However,":[43],"as":[44,235],"proven":[45],"theoretically":[46],"experimentally,":[48],"such":[52],"strongly":[55],"depends":[56],"loss":[59,68,169,186],"function.":[60],"One":[61],"prominent":[64],"approaches":[65],"defining":[67],"functions":[69,170,187],"is":[70,86,223],"set":[72,209],"a":[73,108,127,166,201,208,236],"margin":[74,109,119,198],"between":[75],"positive":[76,138],"negative":[78],"samples":[79],"during":[80],"learning":[82,94],"process.":[83],"This":[84],"task":[85],"particularly":[87],"important":[88],"because":[89],"it":[90],"directly":[91],"affects":[92],"ranking":[96],"triples":[98,139],"ultimately":[100],"defines":[101],"final":[103],"output.":[104],"Approaches":[105],"setting":[107],"following":[112],"challenges:":[113],"a)":[114],"length":[116,195],"has":[120],"be":[122,145],"fixed":[123,128],"manually,":[124],"b)":[125],"without":[126],"point":[129],"center":[131],"margin,":[134],"scores":[136],"are":[140],"not":[141],"necessarily":[142],"enforced":[143],"sufficiently":[146],"small":[147],"fulfill":[149],"translation/rotation":[151],"from":[152],"head":[153],"tail":[155],"by":[156],"using":[157],"relation":[159],"vector.":[160],"In":[161,204],"this":[162],"paper,":[163],"we":[164],"propose":[165],"family":[167],"dubbed":[171],"SlidE":[172],"<sup":[173],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[174],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u00b1</sup>":[175],"address":[177],"aforementioned":[179],"challenges.":[180],"The":[181],"formulation":[182],"proposed":[185],"enables":[188],"an":[189],"automated":[190],"technique":[191],"adjust":[193],"adaptive":[199],"defined":[202],"center.":[203],"our":[205,221],"experiments":[206],"standard":[211],"benchmark":[212],"datasets":[213],"including":[214],"Freebase":[215],"WordNet,":[217],"effectiveness":[219],"approach":[222],"confirmed":[224],"training":[226],"models,":[230],"specifically":[231],"TransE":[232],"RotatE":[234],"case":[237],"study,":[238]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2020-10-08T00:00:00"}