{"id":"https://openalex.org/W3135737375","doi":"https://doi.org/10.1109/tkde.2021.3063985","title":"Scalable Label Propagation for Multi-Relational Learning on the Tensor Product of Graphs","display_name":"Scalable Label Propagation for Multi-Relational Learning on the Tensor Product of Graphs","publication_year":2021,"publication_date":"2021-03-04","ids":{"openalex":"https://openalex.org/W3135737375","doi":"https://doi.org/10.1109/tkde.2021.3063985","mag":"3135737375"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3063985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3063985","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/A5078337006","display_name":"Zhuliu Li","orcid":"https://orcid.org/0000-0003-3978-7974"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhuliu Li","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030259746","display_name":"Raphael Petegrosso","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raphael Petegrosso","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089950471","display_name":"Shaden Smith","orcid":"https://orcid.org/0000-0003-4072-9990"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaden Smith","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082748670","display_name":"David A. Sterling","orcid":"https://orcid.org/0000-0003-4867-7259"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Sterling","raw_affiliation_strings":["Department of Radiation Oncology, University of Minnesota Twin Cities, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, University of Minnesota Twin Cities, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082384108","display_name":"George Karypis","orcid":"https://orcid.org/0000-0003-2753-1437"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Karypis","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066338313","display_name":"Rui Kuang","orcid":"https://orcid.org/0000-0002-4916-903X"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rui Kuang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5078337006"],"corresponding_institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"],"apc_list":null,"apc_paid":null,"fwci":0.6839,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.61336516,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"34","issue":"12","first_page":"5964","last_page":"5978"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9940999746322632,"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":0.9890000224113464,"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":0.7103312611579895},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5947411060333252},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5890941023826599},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.5509495139122009},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.49342861771583557},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43613675236701965},{"id":"https://openalex.org/keywords/tensor-contraction","display_name":"Tensor contraction","score":0.42612335085868835},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.390595018863678},{"id":"https://openalex.org/keywords/tensor-product","display_name":"Tensor product","score":0.32912909984588623},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32383060455322266},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.27773576974868774},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24155107140541077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22477000951766968},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07630735635757446}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7103312611579895},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5947411060333252},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5890941023826599},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.5509495139122009},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.49342861771583557},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43613675236701965},{"id":"https://openalex.org/C124007464","wikidata":"https://www.wikidata.org/wiki/Q428091","display_name":"Tensor contraction","level":3,"score":0.42612335085868835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.390595018863678},{"id":"https://openalex.org/C51255310","wikidata":"https://www.wikidata.org/wiki/Q1163016","display_name":"Tensor product","level":2,"score":0.32912909984588623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32383060455322266},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.27773576974868774},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24155107140541077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22477000951766968},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07630735635757446},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2021.3063985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3063985","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1511885491","https://openalex.org/W1522301498","https://openalex.org/W1527318567","https://openalex.org/W1529533208","https://openalex.org/W1625061074","https://openalex.org/W1630959083","https://openalex.org/W1632866817","https://openalex.org/W1638985343","https://openalex.org/W1814521481","https://openalex.org/W1854251030","https://openalex.org/W1864134408","https://openalex.org/W1866372755","https://openalex.org/W1952825535","https://openalex.org/W1981385563","https://openalex.org/W2017803598","https://openalex.org/W2020804487","https://openalex.org/W2022322548","https://openalex.org/W2024165284","https://openalex.org/W2049588365","https://openalex.org/W2056124433","https://openalex.org/W2108138101","https://openalex.org/W2117587045","https://openalex.org/W2118080949","https://openalex.org/W2122837498","https://openalex.org/W2127957894","https://openalex.org/W2139823104","https://openalex.org/W2153929049","https://openalex.org/W2154455818","https://openalex.org/W2171255489","https://openalex.org/W2346134043","https://openalex.org/W2386495398","https://openalex.org/W2403138661","https://openalex.org/W2538986668","https://openalex.org/W2571268788","https://openalex.org/W2949480905","https://openalex.org/W2963706488","https://openalex.org/W3004555699","https://openalex.org/W3023646171","https://openalex.org/W3122868618","https://openalex.org/W4254313632","https://openalex.org/W6631190155","https://openalex.org/W6636599907","https://openalex.org/W6636705969","https://openalex.org/W6636894223","https://openalex.org/W6638685289","https://openalex.org/W6677111876","https://openalex.org/W6677826147","https://openalex.org/W6678450398","https://openalex.org/W6680434193","https://openalex.org/W6682494755","https://openalex.org/W6704797570","https://openalex.org/W6713353682"],"related_works":["https://openalex.org/W4386687603","https://openalex.org/W1887380982","https://openalex.org/W4307007469","https://openalex.org/W2385280846","https://openalex.org/W2060415987","https://openalex.org/W2140205332","https://openalex.org/W3099936220","https://openalex.org/W2018969011","https://openalex.org/W2519254393","https://openalex.org/W2058488146"],"abstract_inverted_index":{"Multi-relational":[0],"learning":[1,15,75,100],"on":[2,23,139],"knowledge":[3,29],"graphs":[4,30,145],"infers":[5],"high-order":[6,34],"relations":[7,35],"among":[8],"the":[9,12,24,28,33,51,62,87,91,105,108,111,156,164,197],"entities":[10],"across":[11,174,186],"graphs.":[13],"This":[14],"task":[16],"can":[17],"be":[18],"solved":[19],"by":[20,99],"label":[21,47,137,199],"propagation":[22,48,138,200],"tensor":[25,53,113,133,141],"product":[26,54,114,142],"of":[27,90,104,110,143,147,171,182],"to":[31,50,70,162,176],"learn":[32],"as":[36],"a":[37,44,102,119,140],"tensor.":[38],"In":[39],"this":[40],"paper,":[41],"we":[42],"generalize":[43],"widely":[45],"used":[46],"model":[49],"normalized":[52,112],"graph,":[55],"and":[56,61,79,180,204],"propose":[57],"an":[58],"optimization":[59,84],"formulation":[60,85],"scalable":[63],"Low-rank":[64],"Tensor-based":[65],"Label":[66],"Propagation":[67],"algorithm":[68],"(LowrankTLP)":[69],"infer":[71],"multi-relations":[72],"for":[73,95,124],"two":[74],"tasks,":[76],"hyperlink":[77,126],"prediction":[78],"multiple":[80,96,187],"graph":[81,97],"alignment.":[82],"The":[83,189],"minimizes":[86],"upper":[88],"bound":[89,123],"noisy-tensor":[92],"estimating":[93],"error":[94],"alignment,":[98],"with":[101,131,201],"subset":[103],"eigen-pairs":[106],"in":[107,150,155,167],"spectrum":[109],"graph.":[115],"We":[116,128],"also":[117,160],"provide":[118],"data-dependent":[120],"transductive":[121],"Rademacher":[122],"binary":[125],"prediction.":[127],"accelerate":[129],"LowrankTLP":[130,158,193],"parallel":[132],"computation":[134],"which":[135],"enables":[136],"100":[144],"each":[146],"size":[148],"1000":[149],"less":[151],"than":[152],"half":[153],"hour":[154],"simulation.":[157],"was":[159],"applied":[161],"predicting":[163],"author-paper-venue":[165],"hyperlinks":[166],"publication":[168],"records,":[169],"alignment":[170,181],"segmented":[172],"regions":[173],"up":[175],"26":[177],"CT-scan":[178],"images":[179],"protein-protein":[183],"interaction":[184],"networks":[185],"species.":[188],"experiments":[190],"demonstrate":[191],"that":[192],"indeed":[194],"well":[195],"approximates":[196],"original":[198],"better":[202],"scalability":[203],"accuracy.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}