{"id":"https://openalex.org/W4313007581","doi":"https://doi.org/10.1109/tkde.2022.3220625","title":"Contrastive Multi-Modal Knowledge Graph Representation Learning","display_name":"Contrastive Multi-Modal Knowledge Graph Representation Learning","publication_year":2022,"publication_date":"2022-11-08","ids":{"openalex":"https://openalex.org/W4313007581","doi":"https://doi.org/10.1109/tkde.2022.3220625"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3220625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3220625","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Knowledge and Data Engineering","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/A5108683740","display_name":"Quan Fang","orcid":"https://orcid.org/0000-0003-4190-1529"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Quan Fang","raw_affiliation_strings":["National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353447","display_name":"Xiaowei Zhang","orcid":"https://orcid.org/0000-0002-8619-3346"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Zhang","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101766936","display_name":"Jun Hu","orcid":"https://orcid.org/0000-0003-1277-6802"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Hu","raw_affiliation_strings":["National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352418","display_name":"Xian Wu","orcid":"https://orcid.org/0000-0003-1118-9710"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xian Wu","raw_affiliation_strings":["Tencent Medical AI Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent Medical AI Lab, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Xu","raw_affiliation_strings":["National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5108683740"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":4.1651,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.94732286,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"35","issue":"9","first_page":"8983","last_page":"8996"},"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":0.9980999827384949,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.979200005531311,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8256659507751465},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6581641435623169},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6436261534690857},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5775337219238281},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49834537506103516},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4959612786769867},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4951728880405426},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45719683170318604},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.429848849773407},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.42638319730758667},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3816855847835541},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3665071427822113},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24926462769508362}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8256659507751465},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6581641435623169},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6436261534690857},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5775337219238281},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49834537506103516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4959612786769867},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4951728880405426},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45719683170318604},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.429848849773407},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42638319730758667},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3816855847835541},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3665071427822113},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24926462769508362},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2022.3220625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3220625","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1498893086","display_name":null,"funder_award_id":"62036012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2454296646","display_name":null,"funder_award_id":"62106262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G470762236","display_name":null,"funder_award_id":"62072456","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":103,"referenced_works":["https://openalex.org/W68132019","https://openalex.org/W175897666","https://openalex.org/W205829674","https://openalex.org/W1501856433","https://openalex.org/W1522301498","https://openalex.org/W1533230146","https://openalex.org/W1552847225","https://openalex.org/W1599709037","https://openalex.org/W1662382123","https://openalex.org/W1801721664","https://openalex.org/W1989085630","https://openalex.org/W2016753842","https://openalex.org/W2022166150","https://openalex.org/W2094728533","https://openalex.org/W2101848544","https://openalex.org/W2108598243","https://openalex.org/W2116341502","https://openalex.org/W2127795553","https://openalex.org/W2142498761","https://openalex.org/W2184957013","https://openalex.org/W2194775991","https://openalex.org/W2247119764","https://openalex.org/W2250342289","https://openalex.org/W2250635077","https://openalex.org/W2283196293","https://openalex.org/W2432356473","https://openalex.org/W2521492858","https://openalex.org/W2526174222","https://openalex.org/W2586761003","https://openalex.org/W2604314403","https://openalex.org/W2606780347","https://openalex.org/W2612900438","https://openalex.org/W2728059831","https://openalex.org/W2735810033","https://openalex.org/W2752172973","https://openalex.org/W2754524185","https://openalex.org/W2759136286","https://openalex.org/W2774837955","https://openalex.org/W2785761199","https://openalex.org/W2807480793","https://openalex.org/W2887997457","https://openalex.org/W2888572441","https://openalex.org/W2897586972","https://openalex.org/W2907492528","https://openalex.org/W2914592219","https://openalex.org/W2949434543","https://openalex.org/W2950393809","https://openalex.org/W2951105272","https://openalex.org/W2963606508","https://openalex.org/W2963870853","https://openalex.org/W2964007976","https://openalex.org/W2964015378","https://openalex.org/W2969531873","https://openalex.org/W2977897270","https://openalex.org/W2983366375","https://openalex.org/W2988237903","https://openalex.org/W2995448904","https://openalex.org/W2996899616","https://openalex.org/W2997837621","https://openalex.org/W3003265726","https://openalex.org/W3011667710","https://openalex.org/W3034693603","https://openalex.org/W3038934320","https://openalex.org/W3044410371","https://openalex.org/W3091993229","https://openalex.org/W3099387504","https://openalex.org/W3103296573","https://openalex.org/W3114632476","https://openalex.org/W3129758539","https://openalex.org/W3152893301","https://openalex.org/W4287706147","https://openalex.org/W4288102844","https://openalex.org/W4288275971","https://openalex.org/W4294170691","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4300645216","https://openalex.org/W6608344535","https://openalex.org/W6631190155","https://openalex.org/W6631964550","https://openalex.org/W6637178625","https://openalex.org/W6678830454","https://openalex.org/W6681029592","https://openalex.org/W6682691769","https://openalex.org/W6718112784","https://openalex.org/W6726873649","https://openalex.org/W6732510986","https://openalex.org/W6736685754","https://openalex.org/W6737547214","https://openalex.org/W6738964360","https://openalex.org/W6743384090","https://openalex.org/W6745537798","https://openalex.org/W6747772516","https://openalex.org/W6754278344","https://openalex.org/W6754461253","https://openalex.org/W6755573351","https://openalex.org/W6758075616","https://openalex.org/W6766156693","https://openalex.org/W6768179412","https://openalex.org/W6769589523","https://openalex.org/W6770199028","https://openalex.org/W6779518175","https://openalex.org/W6781291478"],"related_works":["https://openalex.org/W4234874385","https://openalex.org/W2081900870","https://openalex.org/W2323648130","https://openalex.org/W2157140558","https://openalex.org/W2378782423","https://openalex.org/W4233308809","https://openalex.org/W2388988621","https://openalex.org/W2357797405","https://openalex.org/W2366623913","https://openalex.org/W4285218279"],"abstract_inverted_index":{"Representation":[0],"learning":[1],"of":[2,57,114,144,176],"knowledge":[3,95],"graphs":[4],"(KGs)":[5],"aims":[6],"to":[7,72,140],"embed":[8],"both":[9],"entities":[10,66,115,145],"and":[11,29,45,62,69,76,116,129,137,146,159,164,179],"relations":[12,49,147],"as":[13,26,52,54],"vectors":[14],"in":[15,67,162],"a":[16,91],"continuous":[17],"low-dimensional":[18],"space,":[19],"which":[20,105],"has":[21],"facilitated":[22],"various":[23],"applications":[24],"such":[25],"link":[27,177],"prediction":[28,178],"entity":[30,124,180],"retrieval.":[31],"Most":[32],"existing":[33,167],"KG":[34],"embedding":[35,97],"methods":[36,169],"focus":[37],"on":[38,170],"modeling":[39],"the":[40,47,55,74,83,157,174],"structured":[41],"fact":[42],"triples":[43,51],"independently":[44],"ignore":[46],"multi-type":[48,160],"among":[50],"well":[53],"variety":[56],"data":[58],"types":[59],"(e.g.,":[60],"texts":[61],"images)":[63],"associated":[64],"with":[65],"KGs,":[68,163],"thus":[70],"fail":[71],"capture":[73],"complex":[75],"multi-modal":[77,111,127],"information":[78],"that":[79,152],"is":[80],"inherently":[81],"inside":[82],"entity-relation":[84],"triples.":[85],"In":[86],"this":[87],"paper,":[88],"we":[89],"propose":[90],"novel":[92],"approach":[93],"for":[94,173],"graph":[96],"named":[98],"Contrastive":[99],"Multi-modal":[100],"Graph":[101],"Neural":[102],"Network":[103],"(CMGNN),":[104],"can":[106,154],"encapsulate":[107],"comprehensive":[108],"features":[109],"from":[110,126,133],"content":[112,128],"descriptions":[113],"high-order":[117,138],"connectivity":[118],"structures.":[119],"Specifically,":[120],"CMGNN":[121,153],"first":[122],"learns":[123],"embeddings":[125],"then":[130],"contrasts":[131],"encodings":[132],"multi-relational":[134],"local":[135],"neighbors":[136],"connectivities":[139],"obtain":[141],"latent":[142],"representations":[143],"simultaneously.":[148],"Experimental":[149],"results":[150],"demonstrate":[151],"effectively":[155],"model":[156],"multi-modalities":[158],"structures":[161],"significantly":[165],"outperforms":[166],"state-of-the-art":[168],"benchmark":[171],"datasets":[172],"tasks":[175],"classification.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":5}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}
