{"id":"https://openalex.org/W3199993187","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533477","title":"Learning Knowledge Graph Embedding in Semantic Space: A Novel Bi-linear Semantic Matching Method","display_name":"Learning Knowledge Graph Embedding in Semantic Space: A Novel Bi-linear Semantic Matching Method","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199993187","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533477","mag":"3199993187"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5038149192","display_name":"Kai Chen","orcid":"https://orcid.org/0000-0003-4160-1024"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Chen","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423424","display_name":"Ye Wang","orcid":"https://orcid.org/0000-0001-7992-3892"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Wang","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103221123","display_name":"Aiping Li","orcid":"https://orcid.org/0000-0003-3335-0093"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aiping Li","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072662599","display_name":"ChenChen Li","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ChenChen Li","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101522255","display_name":"Xiaojuan Zhao","orcid":"https://orcid.org/0000-0003-2623-7586"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojuan Zhao","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000805532","display_name":"Ruidong Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruidong Ding","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5038149192"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63424558,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T10028","display_name":"Topic Modeling","score":0.9990000128746033,"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":0.983299970626831,"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":0.7795515060424805},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.6091952323913574},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6034652590751648},{"id":"https://openalex.org/keywords/semantic-matching","display_name":"Semantic matching","score":0.5848061442375183},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5017199516296387},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4664304554462433},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.4660906195640564},{"id":"https://openalex.org/keywords/vector-space","display_name":"Vector space","score":0.46041256189346313},{"id":"https://openalex.org/keywords/semantic-search","display_name":"Semantic search","score":0.45576012134552},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4535865783691406},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4479764997959137},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4089570641517639},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.40641969442367554},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.38010191917419434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35569819808006287},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12139078974723816}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7795515060424805},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.6091952323913574},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6034652590751648},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.5848061442375183},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5017199516296387},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4664304554462433},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.4660906195640564},{"id":"https://openalex.org/C13336665","wikidata":"https://www.wikidata.org/wiki/Q125977","display_name":"Vector space","level":2,"score":0.46041256189346313},{"id":"https://openalex.org/C166423231","wikidata":"https://www.wikidata.org/wiki/Q1891170","display_name":"Semantic search","level":3,"score":0.45576012134552},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4535865783691406},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4479764997959137},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4089570641517639},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.40641969442367554},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.38010191917419434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35569819808006287},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12139078974723816},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G2498676674","display_name":null,"funder_award_id":"2016QY03D0603,2016QY03D0601,2018YFC0831703,2017YFB0803303,2017YFB100210,2017YFB080330l","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8064468657","display_name":null,"funder_award_id":"61732004,61732022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W205829674","https://openalex.org/W1522301498","https://openalex.org/W1533230146","https://openalex.org/W2081580037","https://openalex.org/W2127795553","https://openalex.org/W2184957013","https://openalex.org/W2187089797","https://openalex.org/W2249040818","https://openalex.org/W2250342289","https://openalex.org/W2250635077","https://openalex.org/W2283196293","https://openalex.org/W2432356473","https://openalex.org/W2728059831","https://openalex.org/W2774837955","https://openalex.org/W2907510403","https://openalex.org/W2946476638","https://openalex.org/W2950393809","https://openalex.org/W2951105272","https://openalex.org/W3034374701","https://openalex.org/W3099387504","https://openalex.org/W6608344535","https://openalex.org/W6631190155","https://openalex.org/W6631964550","https://openalex.org/W6678830454","https://openalex.org/W6686133869","https://openalex.org/W6691327844","https://openalex.org/W6695596964","https://openalex.org/W6718112784","https://openalex.org/W6740216407"],"related_works":["https://openalex.org/W2133831373","https://openalex.org/W2966570129","https://openalex.org/W3099449837","https://openalex.org/W2774861092","https://openalex.org/W4301351852","https://openalex.org/W2281720482","https://openalex.org/W2139549667","https://openalex.org/W2622845166","https://openalex.org/W2315716767","https://openalex.org/W4387489691"],"abstract_inverted_index":{"Knowledge":[0,39],"Graphs":[1],"represent":[2],"facts":[3],"with":[4],"triples":[5,46,109],"containing":[6],"head":[7],"entity":[8,14],"<tex":[9,15,20],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[10,16,21],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$h$</tex>":[11],",":[12],"tail":[13],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$t$</tex>":[17],"and":[18,36,62,73,110,136,189],"relation":[19],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$r$</tex>":[22],"which":[23],"facilitate":[24],"applications":[25],"of":[26,45,71,93,108,132,179,192,199],"many":[27],"scenarios,":[28],"for":[29],"example":[30],"intelligent":[31],"web":[32],"search,":[33],"community":[34],"detection":[35],"question":[37],"answering.":[38],"Graph":[40],"Embedding":[41],"(KGE)":[42],"represents":[43],"elements":[44],"in":[47,142],"a":[48,112],"low-dimensional":[49],"continuous":[50],"vector":[51],"space.":[52,145],"Though":[53],"it":[54],"has":[55],"been":[56],"widely":[57],"studied":[58],"by":[59],"both":[60],"academic":[61],"industry":[63],"communities,":[64],"most":[65],"researches":[66],"focus":[67],"on":[68,162,186],"learning":[69],"embeddings":[70],"entities":[72,89],"relations":[74,87],"separately":[75],"rather":[76],"than":[77],"considering":[78],"the":[79,106,133,139,143,177,180,197],"interactive":[80,101,134,193],"semantic":[81,102,194],"information":[82],"between":[83],"them.":[84],"However,":[85],"neither":[86],"nor":[88],"exist":[90],"lonely":[91],"out":[92],"context.":[94],"In":[95],"this":[96],"paper,":[97],"we":[98,123],"define":[99],"an":[100],"space":[103,195],"to":[104,129,147,158],"model":[105],"context":[107],"propose":[111],"novel":[113],"Bi-linear":[114],"Semantic":[115],"Matching":[116],"Method":[117],"using":[118],"Convolutional":[119],"networks":[120,128],"(BiSC).":[121],"Specifically,":[122],"use":[124],"1D":[125],"convolutional":[126],"neural":[127],"extract":[130],"features":[131],"semantics":[135],"then":[137],"compute":[138],"similarity":[140],"scores":[141],"bi-linear":[144],"Compared":[146],"existing":[148],"complex":[149],"graph":[150],"network":[151],"methods,":[152],"BiSC":[153,182],"needs":[154],"lower":[155],"computational":[156],"cost":[157],"reach":[159],"competitive":[160],"results":[161],"link":[163],"prediction":[164],"task.":[165],"The":[166],"consistent":[167],"state-of-the-art":[168],"performance":[169],"through":[170],"extensive":[171],"experiments":[172],"over":[173],"two":[174],"benchmarks":[175],"demonstrates":[176],"advantages":[178],"proposed":[181],"model.":[183,201],"Further":[184],"analysis":[185],"convergence":[187],"study":[188,191],"case":[190],"show":[196],"efficiency":[198],"our":[200]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}