{"id":"https://openalex.org/W4315630824","doi":"https://doi.org/10.1109/tnnls.2022.3228556","title":"Coarse-to-Fine Contrastive Learning on Graphs","display_name":"Coarse-to-Fine Contrastive Learning on Graphs","publication_year":2023,"publication_date":"2023-01-11","ids":{"openalex":"https://openalex.org/W4315630824","doi":"https://doi.org/10.1109/tnnls.2022.3228556","pmid":"https://pubmed.ncbi.nlm.nih.gov/37018665"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3228556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3228556","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/A5023497333","display_name":"Peiyao Zhao","orcid":"https://orcid.org/0000-0002-0396-2155"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peiyao Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0396-2155","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020554727","display_name":"Yuangang Pan","orcid":"https://orcid.org/0000-0002-7950-4900"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yuangang Pan","raw_affiliation_strings":["A*STAR Center for Frontier AI Research, Fusionopolis, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-7950-4900","affiliations":[{"raw_affiliation_string":"A*STAR Center for Frontier AI Research, Fusionopolis, Singapore","institution_ids":["https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354072","display_name":"Xin Li","orcid":"https://orcid.org/0000-0003-4257-4347"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4257-4347","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101918568","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0001-5299-7074"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5299-7074","affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ivor W. Tsang","orcid":"https://orcid.org/0000-0003-2211-8176"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]},{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["AU","SG"],"is_corresponding":false,"raw_author_name":"Ivor W. Tsang","raw_affiliation_strings":["A*STAR Center for Frontier AI Research, Fusionopolis, Singapore","Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-2211-8176","affiliations":[{"raw_affiliation_string":"A*STAR Center for Frontier AI Research, Fusionopolis, Singapore","institution_ids":["https://openalex.org/I115228651"]},{"raw_affiliation_string":"Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044196762","display_name":"Lejian Liao","orcid":"https://orcid.org/0000-0003-1412-8243"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lejian Liao","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1412-8243","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5023497333"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":1.0225,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80034653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"35","issue":"4","first_page":"4622","last_page":"4634"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9912999868392944,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9678000211715698,"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/discriminative-model","display_name":"Discriminative model","score":0.715508222579956},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6738239526748657},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5590223073959351},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5574178695678711},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5361725091934204},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.526908814907074},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.512969434261322},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.45324862003326416},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.3643602430820465},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36418554186820984}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.715508222579956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6738239526748657},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5590223073959351},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5574178695678711},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5361725091934204},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.526908814907074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.512969434261322},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.45324862003326416},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.3643602430820465},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36418554186820984}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3228556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3228556","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:37018665","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37018665","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":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1888224328","display_name":null,"funder_award_id":"DP200101328","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"},{"id":"https://openalex.org/G2796227307","display_name":null,"funder_award_id":"92270125","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7144638067","display_name":null,"funder_award_id":"62276024","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/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W2027731328","https://openalex.org/W2108862644","https://openalex.org/W2133299088","https://openalex.org/W2154851992","https://openalex.org/W2798991696","https://openalex.org/W2842511635","https://openalex.org/W2907492528","https://openalex.org/W2962756421","https://openalex.org/W3012816161","https://openalex.org/W3021853564","https://openalex.org/W3035524453","https://openalex.org/W3035725276","https://openalex.org/W3036446966","https://openalex.org/W3095746859","https://openalex.org/W3099152386","https://openalex.org/W3104097132","https://openalex.org/W3108655343","https://openalex.org/W3109027749","https://openalex.org/W3118608800","https://openalex.org/W3133518153","https://openalex.org/W3154503084","https://openalex.org/W3160872503","https://openalex.org/W3168925038","https://openalex.org/W3173292968","https://openalex.org/W3188916965","https://openalex.org/W3190214286","https://openalex.org/W4214899340","https://openalex.org/W4220672543","https://openalex.org/W4224229285","https://openalex.org/W4226080570","https://openalex.org/W4281250306","https://openalex.org/W4282942883","https://openalex.org/W4282975557","https://openalex.org/W4283732568","https://openalex.org/W4296437652","https://openalex.org/W4298326742","https://openalex.org/W4309096516","https://openalex.org/W4309413268","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6754278344","https://openalex.org/W6755573351","https://openalex.org/W6756561102","https://openalex.org/W6758854760","https://openalex.org/W6766156693","https://openalex.org/W6779518175","https://openalex.org/W6779940601","https://openalex.org/W6782188741","https://openalex.org/W6783990618","https://openalex.org/W6784694379","https://openalex.org/W6787972765","https://openalex.org/W6790643061","https://openalex.org/W6790763814","https://openalex.org/W6791742336","https://openalex.org/W6796370022"],"related_works":["https://openalex.org/W2011472225","https://openalex.org/W3000057026","https://openalex.org/W3048565508","https://openalex.org/W3163984363","https://openalex.org/W3127142483","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4378713479","https://openalex.org/W2798835721"],"abstract_inverted_index":{"Inspired":[0],"by":[1,32],"the":[2,29,36,52,59,62,67,71,74,78,86,112,140,156,171,183,190],"impressive":[3,43],"success":[4],"of":[5,11,54,61,130,173,185],"contrastive":[6,30],"learning":[7,131],"(CL),":[8],"a":[9,23,127,150],"variety":[10],"graph":[12,37,76,81],"augmentation":[13],"strategies":[14],"have":[15],"been":[16],"employed":[17],"to":[18,35,51,132,138,153,170],"learn":[19],"node":[20,40],"representations":[21],"in":[22],"self-supervised":[24],"manner.":[25],"Existing":[26],"methods":[27],"construct":[28],"samples":[31],"adding":[33],"perturbations":[34,172],"structure":[38],"or":[39],"attributes.":[41],"Although":[42],"results":[44,177],"are":[45],"achieved,":[46],"it":[47],"is":[48],"rather":[49],"blind":[50],"wealth":[53],"prior":[55,105],"information":[56,106,158],"assumed:":[57],"with":[58,189],"increase":[60],"perturbation":[63],"degree":[64],"applied":[65],"on":[66,178],"original":[68,75],"graph:":[69],"1)":[70],"similarity":[72],"between":[73,88],"and":[77,84,165,192],"generated":[79],"augmented":[80,93,145],"gradually":[82,95],"decreases":[83],"2)":[85],"discrimination":[87],"all":[89],"nodes":[90,161],"within":[91],"each":[92],"view":[94],"increases.":[96],"In":[97,120],"this":[98],"article,":[99],"we":[100,122,148],"argue":[101],"that":[102,155],"both":[103],"such":[104],"can":[107,162],"be":[108,163,167],"incorporated":[109],"(differently)":[110],"into":[111],"CL":[113,125],"paradigm":[114,152],"following":[115],"our":[116,186],"general":[117],"ranking":[118,141],"framework.":[119],"particular,":[121],"first":[123],"interpret":[124],"as":[126],"special":[128],"case":[129],"rank":[133],"(L2R),":[134],"which":[135],"inspires":[136],"us":[137],"leverage":[139],"order":[142],"among":[143,159],"positive":[144],"views.":[146],"Meanwhile,":[147],"introduce":[149],"self-ranking":[151],"ensure":[154],"discriminative":[157],"different":[160,174],"maintained":[164],"also":[166],"less":[168],"altered":[169],"degrees.":[175],"Experiment":[176],"various":[179],"benchmark":[180],"datasets":[181],"verify":[182],"effectiveness":[184],"algorithm":[187],"compared":[188],"supervised":[191],"unsupervised":[193],"models.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}