{"id":"https://openalex.org/W4416016562","doi":"https://doi.org/10.1145/3746252.3761109","title":"Dynamic Graph Learning via Historical Information Perception and Multi-Granular Temporal Curriculum Learning","display_name":"Dynamic Graph Learning via Historical Information Perception and Multi-Granular Temporal Curriculum Learning","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416016562","doi":"https://doi.org/10.1145/3746252.3761109"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3761109","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101243677","display_name":"Yuehang Cao","orcid":"https://orcid.org/0000-0002-0415-5064"},"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":"Yuehang Cao","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0415-5064","affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, 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, Changsha, 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, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004606411","display_name":"Yang Fang","orcid":"https://orcid.org/0000-0003-3565-2482"},"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":"Yang Fang","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-3565-2482","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060499624","display_name":"Yan Pan","orcid":"https://orcid.org/0000-0001-8527-6134"},"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":"Yan Pan","raw_affiliation_strings":["National Key Laboratory of Information Systems Engineering, National Key Laboratory of Parallel and Distributed Computing, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-8527-6134","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Information Systems Engineering, National Key Laboratory of Parallel and Distributed Computing, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102717976","display_name":"Jiuyang Tang","orcid":"https://orcid.org/0009-0005-1786-9831"},"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":"Jiuyang Tang","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0009-0005-1786-9831","affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29255193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"189","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8867999911308289,"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":0.8867999911308289,"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":0.014999999664723873,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.013100000098347664,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6898999810218811},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5483999848365784},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46889999508857727},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.39010000228881836},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.36959999799728394},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.33090001344680786},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3273000121116638},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.2989000082015991}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7573000192642212},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6898999810218811},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5789999961853027},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5483999848365784},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46889999508857727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4165000021457672},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.258899986743927},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.2549999952316284},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3761109","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5546835263","display_name":null,"funder_award_id":"2022YFB3102600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2610034660","https://openalex.org/W2765755511","https://openalex.org/W2901504064","https://openalex.org/W2964811671","https://openalex.org/W2998116985","https://openalex.org/W3012774908","https://openalex.org/W4312504137","https://openalex.org/W4385636677"],"related_works":[],"abstract_inverted_index":{"Dynamic":[0],"graph":[1,60,193],"representation":[2,72],"learning":[3,61,134,138,143,151,170,194],"has":[4],"emerged":[5],"as":[6],"a":[7,57,88,93,99,131],"pivotal":[8],"paradigm":[9],"for":[10],"modeling":[11,68],"time-varying":[12],"relational":[13],"patterns":[14],"in":[15,31,82,196],"complex":[16],"systems":[17],"ranging":[18],"from":[19],"social":[20],"networks":[21],"to":[22,144,157,174],"urban":[23],"mobility.":[24],"While":[25],"existing":[26],"methods":[27,195],"achieve":[28],"notable":[29],"progress":[30],"temporal":[32,42,66,100,141,163,168],"modeling,":[33],"one":[34],"critical":[35],"challenge":[36],"remains":[37],"insufficiently":[38],"addressed:":[39],"identifying":[40],"dual":[41],"evolution,":[43],"i,e.,":[44],"instantaneous":[45,119],"states":[46],"and":[47,98,112,120,139],"evolutionary":[48,147],"trajectories.":[49],"To":[50],"address":[51],"the":[52,106,110,115,118,125,185],"challenge,":[53],"we":[54,86,129],"propose":[55,87],"HMGNN,":[56],"novel":[58],"dynamic":[59,89,192],"framework":[62,135],"that":[63,91],"harmoniously":[64],"integrates":[65,92],"dynamics":[67],"with":[69],"stable":[70,159],"structural":[71],"learning,":[73],"allowing":[74],"adaptive":[75],"pattern":[76],"discovery":[77],"while":[78],"preserving":[79],"feature":[80,161],"consistency":[81],"evolving":[83],"environments.":[84],"Firstly,":[85],"model":[90,111,133],"historical":[94,107,121],"information":[95,108,122],"perception":[96],"module":[97,104],"aggregation":[101,126],"module.":[102],"The":[103,149],"converts":[105],"into":[109],"adaptively":[113],"measures":[114],"impact":[116],"of":[117,188,198],"effectively":[123],"through":[124],"function.":[127],"Secondly,":[128],"devise":[130],"dual-component":[132],"comprising":[136],"contrastive":[137,150,155],"multi-granular":[140,167],"curriculum":[142,169],"holistically":[145],"capture":[146],"dynamics.":[148],"component":[152],"employs":[153],"continuous-view":[154],"alignment":[156],"preserve":[158],"node":[160],"across":[162],"evolution.":[164],"Complementarily,":[165],"our":[166],"introduces":[171],"masking":[172],"mechanism":[173],"explicitly":[175],"learn":[176],"different":[177],"time":[178],"interval":[179],"evolution":[180],"patterns.":[181],"Extensive":[182],"experiments":[183],"demonstrate":[184],"significant":[186],"superiority":[187],"HMGNN":[189],"against":[190],"state-of-the-art":[191],"terms":[197],"all":[199],"evaluation":[200],"metrics.":[201]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-08T00:00:00"}