{"id":"https://openalex.org/W4400579181","doi":"https://doi.org/10.1109/tnnls.2024.3406869","title":"Flow to Candidate: Temporal Knowledge Graph Reasoning With Candidate-Oriented Relational Graph","display_name":"Flow to Candidate: Temporal Knowledge Graph Reasoning With Candidate-Oriented Relational Graph","publication_year":2024,"publication_date":"2024-07-12","ids":{"openalex":"https://openalex.org/W4400579181","doi":"https://doi.org/10.1109/tnnls.2024.3406869","pmid":"https://pubmed.ncbi.nlm.nih.gov/38995707"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3406869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3406869","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5102188770","display_name":"Shiqi Fan","orcid":"https://orcid.org/0000-0002-1654-3400"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shiqi Fan","raw_affiliation_strings":["School of Cybersecurity and the School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Cybersecurity and the School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111255248","display_name":"Guoxi Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoxi Fan","raw_affiliation_strings":["School of Mechanical Engineering and the School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and the School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019042214","display_name":"Hongyi Nie","orcid":"https://orcid.org/0000-0001-6371-9168"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyi Nie","raw_affiliation_strings":["School of Mechanical Engineering and the School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and the School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072484211","display_name":"Quanming Yao","orcid":"https://orcid.org/0000-0001-8944-8618"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanming Yao","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078616777","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-7604-8279"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106943753","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0003-2924-946X"},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelong Li","raw_affiliation_strings":["Institute of Artificial Intelligence (TeleAI), China Telecom, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence (TeleAI), China Telecom, Beijing, China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100422377","display_name":"Zhen Wang","orcid":"https://orcid.org/0000-0002-8182-2852"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Wang","raw_affiliation_strings":["School of Cybersecurity and the School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Cybersecurity and the School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5102188770"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":2.0851,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88628369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"36","issue":"4","first_page":"7487","last_page":"7499"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","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/T12292","display_name":"Graph Theory and Algorithms","score":0.9970999956130981,"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"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9819999933242798,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7332646250724792},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5136412978172302},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5097474455833435},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5072750449180603},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4624967575073242},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.4430932402610779},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.4420761466026306},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4114364683628082},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3773185908794403},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35553842782974243}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7332646250724792},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5136412978172302},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5097474455833435},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5072750449180603},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4624967575073242},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.4430932402610779},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.4420761466026306},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4114364683628082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3773185908794403},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35553842782974243},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3406869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3406869","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38995707","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38995707","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G192882225","display_name":null,"funder_award_id":"U22B2036","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2651371037","display_name":null,"funder_award_id":"62203363","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3794980888","display_name":null,"funder_award_id":"11931015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3798114921","display_name":null,"funder_award_id":"171105","funder_id":"https://openalex.org/F4320334945","funder_display_name":"Fok Ying Tong Education Foundation"},{"id":"https://openalex.org/G4668225214","display_name":null,"funder_award_id":"62025602","funder_id":"https://openalex.org/F4320336125","funder_display_name":"National Science Fund for Distinguished Young Scholars"},{"id":"https://openalex.org/G4823467430","display_name":null,"funder_award_id":"D5000230366","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G870971120","display_name":null,"funder_award_id":"2022ZD0160300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320334945","display_name":"Fok Ying Tong Education Foundation","ror":"https://ror.org/01mv9t934"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320336125","display_name":"National Science Fund for Distinguished Young Scholars","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W2000967095","https://openalex.org/W2250225488","https://openalex.org/W2604314403","https://openalex.org/W2788284887","https://openalex.org/W2798864014","https://openalex.org/W2889782235","https://openalex.org/W2899964298","https://openalex.org/W2907492528","https://openalex.org/W2950635152","https://openalex.org/W2958089299","https://openalex.org/W3003265726","https://openalex.org/W3081182976","https://openalex.org/W3109074851","https://openalex.org/W3167197358","https://openalex.org/W3171160983","https://openalex.org/W3188263062","https://openalex.org/W3194344375","https://openalex.org/W3202900983","https://openalex.org/W3209694784","https://openalex.org/W4214899340","https://openalex.org/W4224317449","https://openalex.org/W4280649755","https://openalex.org/W4287815536","https://openalex.org/W4312278436","https://openalex.org/W4317796230","https://openalex.org/W4318823771","https://openalex.org/W4367048240","https://openalex.org/W4377971427","https://openalex.org/W4380303532","https://openalex.org/W4385269012","https://openalex.org/W4385567036","https://openalex.org/W4389519294","https://openalex.org/W4390005328","https://openalex.org/W4391547592","https://openalex.org/W4393260925","https://openalex.org/W6622957738","https://openalex.org/W6631964550","https://openalex.org/W6678830454","https://openalex.org/W6718112784","https://openalex.org/W6741591689","https://openalex.org/W6745779156","https://openalex.org/W6769589523","https://openalex.org/W6771247989","https://openalex.org/W6771929373","https://openalex.org/W6773885729","https://openalex.org/W6783641038","https://openalex.org/W6787811871","https://openalex.org/W6787861618","https://openalex.org/W6788834500","https://openalex.org/W6791751402","https://openalex.org/W6796465120","https://openalex.org/W6797333116","https://openalex.org/W6799315359","https://openalex.org/W6801300823","https://openalex.org/W6804136563","https://openalex.org/W6810458228","https://openalex.org/W6847371435","https://openalex.org/W6863124549","https://openalex.org/W6867907617"],"related_works":["https://openalex.org/W3181676408","https://openalex.org/W1549959306","https://openalex.org/W320292658","https://openalex.org/W2186138942","https://openalex.org/W2806326686","https://openalex.org/W2001007279","https://openalex.org/W2079674650","https://openalex.org/W2945061532","https://openalex.org/W2389834944","https://openalex.org/W191987727"],"abstract_inverted_index":{"Reasoning":[0],"over":[1],"temporal":[2,156],"knowledge":[3,43],"graphs":[4,44,121,172,186],"(TKGs)":[5],"is":[6,161],"a":[7,98,107,131,134,153,177,196,211,268],"challenging":[8],"task":[9,32],"that":[10,181,249],"requires":[11],"models":[12],"to":[13,34,38,62,111,122,139,203,215],"infer":[14],"future":[15],"events":[16],"based":[17,83],"on":[18,84,234,244],"past":[19],"facts.":[20],"Currently,":[21],"subgraph-based":[22,109],"methods":[23,49,71],"have":[24,50],"become":[25],"the":[26,85,124,141,164,188,200,205,217,223,260],"state-of-the-art":[27],"(SOTA)":[28],"techniques":[29],"for":[30,271,279],"this":[31,103],"due":[33],"their":[35],"superior":[36],"capability":[37],"explore":[39],"local":[40,125,189],"information":[41,96,144],"in":[42,53,57,187,191,199],"(KGs).":[45],"However,":[46],"while":[47],"previous":[48],"been":[51],"effective":[52],"capturing":[54],"semantic":[55],"patterns":[56,82],"TKG,":[58],"they":[59],"are":[60],"hard":[61],"capture":[63,74,112,123,204],"more":[64,95],"complex":[65,113],"topological":[66],"patterns.":[67,115],"In":[68,148,263],"contrast,":[69],"path-based":[70],"can":[72,92,182],"efficiently":[73],"relation":[75,81,88],"paths":[76],"between":[77,145],"nodes":[78],"and":[79,129,167,221,241,256],"obtain":[80],"order":[86],"of":[87,127,133],"connections.":[89],"But":[90],"subgraphs":[91],"retain":[93],"much":[94],"than":[97,259],"single":[99],"path.":[100],"Motivated":[101],"by":[102],"observation,":[104],"we":[105,150,175,194,209,230],"propose":[106,176],"new":[108],"approach":[110,252],"relational":[114,120,171,185,269],"The":[116],"method":[117,266],"constructs":[118],"candidate-oriented":[119,170],"structure":[126,143],"TKGs":[128],"introduces":[130],"variant":[132],"graph":[135,142,270],"neural":[136],"network":[137],"model":[138],"learn":[140],"query-candidate":[146,273],"pairs.":[147],"particular,":[149],"first":[151],"design":[152,210],"prior":[154],"directed":[155],"edge":[157],"sampling":[158],"method,":[159],"which":[160,275],"starting":[162],"from":[163],"query":[165],"node":[166],"generating":[168],"multiple":[169],"simultaneously.":[173],"Next,":[174],"recursive":[178],"propagation":[179,201],"architecture":[180,202],"encode":[183],"all":[184],"structures":[190],"parallel.":[192],"Additionally,":[193],"introduce":[195],"self-attention":[197],"mechanism":[198],"query's":[206],"preference.":[207],"Finally,":[208],"simple":[212],"scoring":[213],"function":[214],"calculate":[216],"candidate":[218],"nodes'":[219],"scores":[220],"generate":[222],"model's":[224],"predictions.":[225],"To":[226],"validate":[227],"our":[228,250,265],"approach,":[229],"conduct":[231],"extensive":[232],"experiments":[233],"four":[235,245],"benchmark":[236,246],"datasets":[237,247],"(ICEWS14,":[238],"ICEWS18,":[239],"ICEWS0515,":[240],"YAGO).":[242],"Experiments":[243],"demonstrate":[248],"proposed":[251],"possesses":[253],"stronger":[254],"inference":[255],"faster":[257],"convergence":[258],"SOTA":[261],"methods.":[262],"addition,":[264],"provides":[267],"each":[272],"pair,":[274],"offers":[276],"interpretable":[277],"evidence":[278],"TKG":[280],"prediction":[281],"results.":[282]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}