{"id":"https://openalex.org/W4400485594","doi":"https://doi.org/10.3390/e26070588","title":"Effective Temporal Graph Learning via Personalized PageRank","display_name":"Effective Temporal Graph Learning via Personalized PageRank","publication_year":2024,"publication_date":"2024-07-10","ids":{"openalex":"https://openalex.org/W4400485594","doi":"https://doi.org/10.3390/e26070588","pmid":"https://pubmed.ncbi.nlm.nih.gov/39056950"},"language":"en","primary_location":{"id":"doi:10.3390/e26070588","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26070588","pdf_url":"https://www.mdpi.com/1099-4300/26/7/588/pdf?version=1720614158","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/26/7/588/pdf?version=1720614158","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111252945","display_name":"Ziyu Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Liao","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing 400715, China"],"raw_orcid":"https://orcid.org/0009-0006-0662-7244","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing 400715, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103286422","display_name":"Tao Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Liu","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing 400715, China"],"raw_orcid":"https://orcid.org/0009-0009-1267-3038","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing 400715, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100298067","display_name":"Yue He","orcid":"https://orcid.org/0009-0000-4807-690X"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue He","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing 400715, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing 400715, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101021504","display_name":"Longlong Lin","orcid":"https://orcid.org/0000-0002-2194-8146"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Longlong Lin","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing 400715, China"],"raw_orcid":"https://orcid.org/0000-0002-2194-8146","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing 400715, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101021504"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":1.8881,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.87589325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"26","issue":"7","first_page":"588","last_page":"588"},"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/pagerank","display_name":"PageRank","score":0.8528867959976196},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6980832815170288},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.665480375289917},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5934995412826538},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5358219146728516},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.505865752696991},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4701283872127533},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.4664708077907562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36795246601104736}],"concepts":[{"id":"https://openalex.org/C2779172887","wikidata":"https://www.wikidata.org/wiki/Q184316","display_name":"PageRank","level":2,"score":0.8528867959976196},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6980832815170288},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.665480375289917},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5934995412826538},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5358219146728516},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.505865752696991},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4701283872127533},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.4664708077907562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36795246601104736},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e26070588","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26070588","pdf_url":"https://www.mdpi.com/1099-4300/26/7/588/pdf?version=1720614158","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:39056950","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39056950","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11275858","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11275858","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11275858/pdf/entropy-26-00588.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:784d0e88a3364c0f84c0997dc77b5fd2","is_oa":true,"landing_page_url":"https://doaj.org/article/784d0e88a3364c0f84c0997dc77b5fd2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 26, Iss 7, p 588 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/e26070588","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26070588","pdf_url":"https://www.mdpi.com/1099-4300/26/7/588/pdf?version=1720614158","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G288908271","display_name":null,"funder_award_id":"CXQT21005","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4195643339","display_name":null,"funder_award_id":"SWU-XDJH202303","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7479091967","display_name":null,"funder_award_id":"SWU-KQ22028","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320323711","display_name":"Southwest University","ror":"https://ror.org/01kj4z117"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400485594.pdf"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2084809122","https://openalex.org/W2138157561","https://openalex.org/W2154851992","https://openalex.org/W2294347342","https://openalex.org/W2387462954","https://openalex.org/W2393319904","https://openalex.org/W2519887557","https://openalex.org/W2610034660","https://openalex.org/W2623187518","https://openalex.org/W2788614083","https://openalex.org/W2795735740","https://openalex.org/W2798918712","https://openalex.org/W2808908091","https://openalex.org/W2901504064","https://openalex.org/W2903329593","https://openalex.org/W2912636151","https://openalex.org/W2962756421","https://openalex.org/W2963224980","https://openalex.org/W2986068433","https://openalex.org/W2998116985","https://openalex.org/W3002028984","https://openalex.org/W3007813770","https://openalex.org/W3026076535","https://openalex.org/W3037528720","https://openalex.org/W3098702884","https://openalex.org/W3102554291","https://openalex.org/W3103254545","https://openalex.org/W3104097132","https://openalex.org/W3128191059","https://openalex.org/W3128443161","https://openalex.org/W3160800264","https://openalex.org/W3168735469","https://openalex.org/W3189882732","https://openalex.org/W3207061671","https://openalex.org/W3214753197","https://openalex.org/W4226280392","https://openalex.org/W4306959790","https://openalex.org/W4381744351","https://openalex.org/W4382240020","https://openalex.org/W4392744976","https://openalex.org/W4394685238","https://openalex.org/W4396601642","https://openalex.org/W4396759418","https://openalex.org/W4399419059","https://openalex.org/W4401863181","https://openalex.org/W6749982562","https://openalex.org/W6759226055","https://openalex.org/W6767427508","https://openalex.org/W6776137863","https://openalex.org/W6786422567","https://openalex.org/W6790520858","https://openalex.org/W6847201694","https://openalex.org/W6866358263"],"related_works":["https://openalex.org/W3206528106","https://openalex.org/W3036264823","https://openalex.org/W2912814903","https://openalex.org/W2123605750","https://openalex.org/W2088740331","https://openalex.org/W3038102983","https://openalex.org/W2950907416","https://openalex.org/W1559483280","https://openalex.org/W2082479932","https://openalex.org/W2932872266"],"abstract_inverted_index":{"Graph":[0],"representation":[1,30,38,111,196],"learning":[2,31,112,197],"aims":[3],"to":[4,43,51,89,155,159],"map":[5],"nodes":[6],"or":[7,151],"edges":[8],"within":[9],"a":[10,108,186],"graph":[11,29,104,110,195],"using":[12],"low-dimensional":[13],"vectors,":[14],"while":[15],"preserving":[16],"as":[17,21,171,183,185],"much":[18],"topological":[19],"information":[20,66],"possible.":[22],"During":[23],"past":[24],"decades,":[25],"numerous":[26],"algorithms":[27,198],"for":[28,79,163],"have":[32,40],"emerged.":[33],"Among":[34],"them,":[35],"proximity":[36],"matrix":[37,81,117,202],"methods":[39,78],"been":[41],"shown":[42],"exhibit":[44],"excellent":[45],"performance":[46],"in":[47,140],"experiments":[48,167],"and":[49,93,176],"scale":[50,72],"large":[52],"graphs":[53],"with":[54,59,188],"millions":[55],"of":[56,63,73,102,119,128],"nodes.":[57],"However,":[58],"the":[60,64,71,99,116],"rapid":[61],"development":[62],"Internet,":[65],"interactions":[67],"are":[68],"happening":[69],"at":[70],"billions":[74],"every":[75],"moment.":[76],"Most":[77],"similarity":[80,91],"factorization":[82,118,203],"still":[83],"focus":[84],"on":[85,115,144,168,200,208],"static":[86],"graphs,":[87,182],"leading":[88],"incomplete":[90],"descriptions":[92],"low":[94],"embedding":[95,100,161],"quality.":[96],"To":[97],"enhance":[98],"quality":[101],"temporal":[103,109,134,141,181,210],"learning,":[105],"we":[106,146,192],"propose":[107],"model":[113],"based":[114,199],"Time-constrained":[120],"Personalize":[121],"PageRank":[122,130],"(TPPR)":[123],"matrices.":[124],"TPPR,":[125],"an":[126],"extension":[127],"personalized":[129],"(PPR)":[131],"that":[132,194],"incorporates":[133],"information,":[135],"better":[136],"captures":[137],"node":[138,174,177],"similarities":[139],"graphs.":[142],"Based":[143],"this,":[145],"use":[147],"Single":[148],"Value":[149],"Decomposition":[150],"Nonnegative":[152],"Matrix":[153],"Factorization":[154],"decompose":[156],"TPPR":[157,201],"matrices":[158],"obtain":[160],"vectors":[162],"each":[164],"node.":[165],"Through":[166],"tasks":[169],"such":[170],"link":[172],"prediction,":[173],"classification,":[175],"clustering":[178],"across":[179],"multiple":[180,209],"well":[184],"comparison":[187],"various":[189],"experimental":[190],"methods,":[191],"find":[193],"achieve":[204],"overall":[205],"outstanding":[206],"scores":[207],"datasets,":[211],"highlighting":[212],"their":[213],"effectiveness.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}