{"id":"https://openalex.org/W3106720267","doi":"https://doi.org/10.1109/jiot.2020.3039750","title":"Convolutional Network Embedding of Text-Enhanced Representation for Knowledge Graph Completion","display_name":"Convolutional Network Embedding of Text-Enhanced Representation for Knowledge Graph Completion","publication_year":2020,"publication_date":"2020-11-23","ids":{"openalex":"https://openalex.org/W3106720267","doi":"https://doi.org/10.1109/jiot.2020.3039750","mag":"3106720267"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2020.3039750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2020.3039750","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-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/A5073659320","display_name":"Feng Zhao","orcid":"https://orcid.org/0000-0001-7205-3302"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Zhao","raw_affiliation_strings":["National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081656092","display_name":"Tao Xu","orcid":"https://orcid.org/0000-0002-5783-6859"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Xu","raw_affiliation_strings":["National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038229289","display_name":"Langjunqing Jin","orcid":"https://orcid.org/0000-0001-9784-7352"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Langjunqing Jin","raw_affiliation_strings":["National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022262922","display_name":"Hai Jin","orcid":"https://orcid.org/0000-0002-3934-7605"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Jin","raw_affiliation_strings":["National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073659320"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":1.9884,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.89354245,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":"23","first_page":"16758","last_page":"16769"},"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":0.9987000226974487,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9883000254631042,"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":0.8063913583755493},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.5572399497032166},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5220468044281006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46679550409317017},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43298354744911194},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.42818552255630493},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41853445768356323},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.4128604531288147},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.353241890668869},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3362904191017151},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32681652903556824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8063913583755493},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.5572399497032166},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5220468044281006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46679550409317017},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43298354744911194},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.42818552255630493},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41853445768356323},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.4128604531288147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.353241890668869},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3362904191017151},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32681652903556824}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2020.3039750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2020.3039750","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.75}],"awards":[{"id":"https://openalex.org/G1132394673","display_name":null,"funder_award_id":"2018YFB1404302","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G949712564","display_name":null,"funder_award_id":"62072203","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":55,"referenced_works":["https://openalex.org/W167809298","https://openalex.org/W205829674","https://openalex.org/W1533230146","https://openalex.org/W1614298861","https://openalex.org/W1832693441","https://openalex.org/W2127426251","https://openalex.org/W2127795553","https://openalex.org/W2153579005","https://openalex.org/W2155454737","https://openalex.org/W2158028897","https://openalex.org/W2158139315","https://openalex.org/W2184957013","https://openalex.org/W2247119764","https://openalex.org/W2249040818","https://openalex.org/W2250342289","https://openalex.org/W2250521169","https://openalex.org/W2250635077","https://openalex.org/W2250807343","https://openalex.org/W2251103205","https://openalex.org/W2251182116","https://openalex.org/W2251363251","https://openalex.org/W2283196293","https://openalex.org/W2336384382","https://openalex.org/W2468628149","https://openalex.org/W2499696929","https://openalex.org/W2514852614","https://openalex.org/W2517194566","https://openalex.org/W2522332826","https://openalex.org/W2558476738","https://openalex.org/W2567619939","https://openalex.org/W2571811098","https://openalex.org/W2579831760","https://openalex.org/W2728059831","https://openalex.org/W2739322222","https://openalex.org/W2774837955","https://openalex.org/W2963606508","https://openalex.org/W2963688791","https://openalex.org/W2964116313","https://openalex.org/W3100809613","https://openalex.org/W4294170691","https://openalex.org/W6608344535","https://openalex.org/W6678830454","https://openalex.org/W6678846912","https://openalex.org/W6682691769","https://openalex.org/W6683461794","https://openalex.org/W6683557909","https://openalex.org/W6686133869","https://openalex.org/W6691327844","https://openalex.org/W6691723933","https://openalex.org/W6695596964","https://openalex.org/W6703471893","https://openalex.org/W6724366048","https://openalex.org/W6731817843","https://openalex.org/W6732517699","https://openalex.org/W6740216407"],"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/W1849827364","https://openalex.org/W2786299737","https://openalex.org/W115324854","https://openalex.org/W4211187494"],"abstract_inverted_index":{"In":[0,95],"recent":[1],"years,":[2],"knowledge":[3,23,43,53,64,69,86,90,156,186],"graph":[4,91,187],"representation":[5,44,103,146,174,201],"learning":[6,12,104],"has":[7,244],"prompted":[8],"extensive":[9],"research.":[10],"Machine":[11],"models":[13],"are":[14],"used":[15,169],"to":[16,25,31,61,170,180],"map":[17],"entity":[18,149,205],"and":[19,33,49,77,84,111,158,178,184,206,216,225,243],"relational":[20],"data":[21,118,231],"in":[22,28,52,153],"graphs":[24,54],"vector":[26,152,202],"representations":[27],"low-dimensional":[29],"spaces":[30],"predict":[32],"analyze":[34],"potential":[35],"relationships.":[36],"Current":[37],"works":[38],"mainly":[39],"focus":[40],"on":[41,130,219],"the":[42,46,67,131,134,138,145,148,154,164,172,185,192,195,199,204,207,220,240],"of":[45,141,147,176,194,198,203,247],"triple":[47,217],"structure":[48,151],"relationship":[50,150],"path":[51],"without":[55],"fully":[56],"utilizing":[57],"external":[58],"textual":[59],"information":[60,110,115],"semantically":[62],"supplement":[63],"representation.":[65],"However,":[66],"existing":[68,155],"inventory,":[70],"such":[71,212],"as":[72,213],"that":[73,106,234],"for":[74],"smart":[75],"health":[76],"emotion":[78],"care":[79],"systems,":[80],"is":[81,87,93,168,188],"relatively":[82],"meager,":[83],"structural":[85],"incomplete;":[88],"therefore,":[89],"completion":[92],"essential.":[94],"this":[96],"article,":[97],"we":[98],"propose":[99],"a":[100,121],"novel":[101],"joint":[102,173,200],"model":[105,136,236,242],"introduces":[107],"text":[108,117],"description":[109],"extracts":[112],"reliable":[113],"feature":[114],"from":[116],"by":[119,190],"using":[120],"convolutional":[122],"neural":[123],"network":[124],"(CNN)":[125],"model.":[126],"Furthermore,":[127],"being":[128],"based":[129],"attention":[132],"mechanism,":[133],"proposed":[135],"distinguishes":[137],"characteristic":[139],"credibility":[140],"different":[142],"relationships,":[143],"enhances":[144],"graph,":[157],"obtains":[159],"rich":[160],"semantic":[161],"information.":[162],"Finally,":[163],"2-D":[165],"convolution":[166],"operation":[167],"process":[171],"vectors":[175],"entities":[177],"relationships":[179],"obtain":[181],"nonlinear":[182],"features,":[183],"completed":[189],"completing":[191],"calculation":[193],"score":[196],"function":[197],"relationship.":[208],"Experiments":[209],"performing":[210],"tasks,":[211],"link":[214],"prediction":[215],"classification,":[218],"FreeBase":[221],"(FB15k),":[222],"WordNet":[223],"(WN18)":[224],"Yet":[226],"Another":[227],"Great":[228],"Ontology":[229],"(YAGO3-10)":[230],"sets":[232],"reveal":[233],"our":[235],"performs":[237],"better":[238],"than":[239],"benchmark":[241],"some":[245],"degree":[246],"scalability.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}