{"id":"https://openalex.org/W4367047175","doi":"https://doi.org/10.1145/3543507.3583246","title":"Graph Self-supervised Learning with Augmentation-aware Contrastive Learning","display_name":"Graph Self-supervised Learning with Augmentation-aware Contrastive Learning","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367047175","doi":"https://doi.org/10.1145/3543507.3583246"},"language":"en","primary_location":{"id":"doi:10.1145/3543507.3583246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583246","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583246","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583246","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100319452","display_name":"Dong Chen","orcid":"https://orcid.org/0000-0002-0526-9346"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Chen","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-0526-9346","affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014937762","display_name":"Xiang Zhao","orcid":"https://orcid.org/0000-0001-6339-0219"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Zhao","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-6339-0219","affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391888","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-1568-2396"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Data Science and Analytics Thrust, Information Hub, The Hong Kong University of Science and Technology (Guangzhou), China"],"raw_orcid":"https://orcid.org/0000-0002-1568-2396","affiliations":[{"raw_affiliation_string":"Data Science and Analytics Thrust, Information Hub, The Hong Kong University of Science and Technology (Guangzhou), China","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060371329","display_name":"Zhen Tan","orcid":"https://orcid.org/0000-0001-8643-4683"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Tan","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-8643-4683","affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106942630","display_name":"Weidong Xiao","orcid":"https://orcid.org/0000-0002-6957-3769"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Xiao","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-6957-3769","affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7382,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.86490041,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"154","last_page":"164"},"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/T10269","display_name":"Epigenetics and DNA Methylation","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9839000105857849,"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":0.7925139665603638},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6689022183418274},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6430578827857971},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6410393118858337},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6015153527259827},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5913720726966858},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5411490797996521},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4539702534675598},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4003527760505676},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2163817584514618},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1943700611591339},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08133643865585327}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7925139665603638},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6689022183418274},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6430578827857971},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6410393118858337},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6015153527259827},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5913720726966858},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5411490797996521},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4539702534675598},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4003527760505676},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2163817584514618},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1943700611591339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08133643865585327},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3543507.3583246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583246","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583246","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-127388","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-127388","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":{"id":"doi:10.1145/3543507.3583246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583246","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583246","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6899999976158142}],"awards":[{"id":"https://openalex.org/G2605822748","display_name":null,"funder_award_id":"U19B2024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5904781070","display_name":null,"funder_award_id":"71971212","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8218347068","display_name":null,"funder_award_id":"62272469","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/F4320323537","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4367047175.pdf","grobid_xml":"https://content.openalex.org/works/W4367047175.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W2154851992","https://openalex.org/W2946829651","https://openalex.org/W3011574394","https://openalex.org/W3012816161","https://openalex.org/W3035524453","https://openalex.org/W3036446966","https://openalex.org/W3088409176","https://openalex.org/W3093957844","https://openalex.org/W3095602948","https://openalex.org/W3099152386","https://openalex.org/W3101397996","https://openalex.org/W3104097132","https://openalex.org/W3194259208","https://openalex.org/W3203774379","https://openalex.org/W4224324140","https://openalex.org/W6784694379","https://openalex.org/W6959643953"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W3166049060","https://openalex.org/W4311865232","https://openalex.org/W2904380457"],"abstract_inverted_index":{"Graph":[0,73],"self-supervised":[1],"learning":[2,26,32,125,150],"aims":[3],"to":[4,17,27,57,128,134],"mine":[5],"useful":[6],"information":[7,107],"from":[8,34,108],"unlabeled":[9],"graph":[10,19,37,43],"data,":[11],"and":[12,53,59,171],"has":[13],"been":[14],"successfully":[15],"applied":[16],"pre-train":[18],"representations.":[20,65],"Many":[21],"existing":[22],"approaches":[23],"use":[24,104],"contrastive":[25,44,124],"learn":[28],"powerful":[29],"embeddings":[30],"by":[31],"contrastively":[33],"two":[35],"augmented":[36],"views.":[38],"However,":[39],"none":[40],"of":[41,50,63,105,160,178],"these":[42],"methods":[45,170],"fully":[46],"exploits":[47],"the":[48,86,89,106,109,123,143,149],"diversity":[49,95],"different":[51,135],"augmentations,":[52],"hence":[54],"is":[55,83],"prone":[56],"overfitting":[58],"limited":[60],"generalization":[61,99],"ability":[62],"learned":[64],"In":[66],"this":[67,113,152],"paper,":[68],"we":[69,138],"propose":[70],"a":[71,158,176],"novel":[72],"Self-supervised":[74],"Learning":[75],"method":[76,82,167],"with":[77,122],"Augmentation-aware":[78],"Contrastive":[79],"Learning.":[80],"Our":[81],"based":[84],"on":[85,142],"finding":[87],"that":[88,165],"pre-trained":[90],"model":[91],"after":[92],"adding":[93],"augmentation":[94,111],"can":[96,154],"achieve":[97],"better":[98,173],"ability.":[100],"To":[101],"make":[102],"full":[103],"diverse":[110],"method,":[112],"paper":[114],"constructs":[115],"new":[116],"augmentation-aware":[117],"prediction":[118],"task":[119],"which":[120],"complementary":[121],"task.":[126],"Similar":[127],"how":[129],"pre-training":[130],"requires":[131],"fast":[132],"adaptation":[133,141],"downstream":[136,179],"tasks,":[137],"simulate":[139],"train-test":[140],"constructed":[144],"tasks":[145],"for":[146,175],"further":[147],"enhancing":[148],"ability;":[151],"strategy":[153],"be":[155],"deemed":[156],"as":[157],"form":[159],"meta-learning.":[161],"Experimental":[162],"results":[163],"show":[164],"our":[166],"outperforms":[168],"previous":[169],"learns":[172],"representations":[174],"variety":[177],"tasks.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
