{"id":"https://openalex.org/W4409671356","doi":"https://doi.org/10.1145/3696410.3714943","title":"Ranking on Dynamic Graphs: An Effective and Robust Band-Pass Disentangled Approach","display_name":"Ranking on Dynamic Graphs: An Effective and Robust Band-Pass Disentangled Approach","publication_year":2025,"publication_date":"2025-04-22","ids":{"openalex":"https://openalex.org/W4409671356","doi":"https://doi.org/10.1145/3696410.3714943"},"language":"en","primary_location":{"id":"doi:10.1145/3696410.3714943","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714943","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714943","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","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/10.1145/3696410.3714943","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yingxuan Li","orcid":"https://orcid.org/0009-0000-1518-8040"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingxuan Li","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0000-1518-8040","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100704963","display_name":"Yuanyuan Xu","orcid":"https://orcid.org/0000-0001-7147-4498"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yuanyuan Xu","raw_affiliation_strings":["University of New South Wales, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0001-7147-4498","affiliations":[{"raw_affiliation_string":"University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079659938","display_name":"Xuemin Lin","orcid":"https://orcid.org/0000-0003-2396-7225"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuemin Lin","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-2396-7225","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385498","display_name":"Wenjie Zhang","orcid":"https://orcid.org/0000-0001-6572-2600"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wenjie Zhang","raw_affiliation_strings":["University of New South Wales, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0001-6572-2600","affiliations":[{"raw_affiliation_string":"University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100386104","display_name":"Ying Zhang","orcid":"https://orcid.org/0000-0002-2674-1638"},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Zhang","raw_affiliation_strings":["Zhejiang Gongshang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2674-1638","affiliations":[{"raw_affiliation_string":"Zhejiang Gongshang University, Hangzhou, China","institution_ids":["https://openalex.org/I75059550"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.5674,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.97746782,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3918","last_page":"3929"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","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"}},"topics":[{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9858999848365784,"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/T12288","display_name":"Optimization and Search Problems","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.5932953953742981},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5921208262443542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3462603986263275}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5932953953742981},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5921208262443542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3462603986263275}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3696410.3714943","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714943","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714943","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3696410.3714943","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714943","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714943","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G8764403337","display_name":null,"funder_award_id":"U2241211","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409671356.pdf","grobid_xml":"https://content.openalex.org/works/W4409671356.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W131619556","https://openalex.org/W2005697854","https://openalex.org/W2008832322","https://openalex.org/W2101491865","https://openalex.org/W2108862644","https://openalex.org/W2235780046","https://openalex.org/W2669485504","https://openalex.org/W2744043447","https://openalex.org/W2808955427","https://openalex.org/W2893230400","https://openalex.org/W2908404712","https://openalex.org/W2951086007","https://openalex.org/W2965683718","https://openalex.org/W2990138404","https://openalex.org/W2998313947","https://openalex.org/W3109841242","https://openalex.org/W3123329971","https://openalex.org/W3125785968","https://openalex.org/W3155874371","https://openalex.org/W3190794503","https://openalex.org/W3206604724","https://openalex.org/W3209048663","https://openalex.org/W4206503836","https://openalex.org/W4220779330","https://openalex.org/W4225512856","https://openalex.org/W4242535057","https://openalex.org/W4285451014","https://openalex.org/W4286750969","https://openalex.org/W4312648479","https://openalex.org/W4366492495","https://openalex.org/W4367046824","https://openalex.org/W4367046975","https://openalex.org/W4380353914","https://openalex.org/W4380433123","https://openalex.org/W4385562479","https://openalex.org/W4386075642","https://openalex.org/W4386075991","https://openalex.org/W4389539847","https://openalex.org/W4393160226","https://openalex.org/W4396735777","https://openalex.org/W4396758529","https://openalex.org/W4396758697","https://openalex.org/W4396759418","https://openalex.org/W4396817313","https://openalex.org/W4401857076","https://openalex.org/W4401857147","https://openalex.org/W4401857350","https://openalex.org/W4401857377","https://openalex.org/W4401863466","https://openalex.org/W4401863538","https://openalex.org/W4409657429","https://openalex.org/W6600339963","https://openalex.org/W6609501977"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Ranking":[0,152],"is":[1],"an":[2,189],"essential":[3],"and":[4,45,83,114,160,166],"practical":[5],"task":[6],"on":[7],"dynamic":[8,90],"graphs,":[9],"which":[10,38,60,105],"aims":[11],"to":[12,33,40,50,62,69,121,155,175],"prioritize":[13],"future":[14],"interaction":[15],"candidates":[16],"for":[17,89,136],"given":[18],"queries.":[19],"While":[20],"existing":[21],"solutions":[22],"achieve":[23],"promising":[24],"ranking":[25,87],"performance,":[26],"they":[27,46],"leverage":[28],"a":[29,56,81,99,149],"single":[30],"listwise":[31],"loss":[32,154],"jointly":[34,156],"optimize":[35,157],"candidate":[36,158],"sets,":[37],"leads":[39],"the":[41,70,93,177],"gradient":[42,178],"vanishing":[43,179],"issue;":[44],"employ":[47],"neural":[48],"networks":[49],"model":[51,122],"complex":[52,107],"temporal":[53,66,108,137],"structures":[54,109,138],"within":[55],"shared":[57],"latent":[58],"space,":[59],"fails":[61],"accurately":[63],"capture":[64],"multi-scale":[65,134,142],"patterns":[67],"due":[68],"frequency":[71,94,112],"aliasing":[72],"issue.":[73,180],"To":[74],"address":[75],"these":[76],"issues,":[77],"we":[78,97,147,170],"propose":[79,98],"BandRank,":[80],"novel":[82],"robust":[84,150],"band-pass":[85,100],"disentangled":[86,101],"approach":[88,131],"graphs":[91],"in":[92],"domain.":[95],"Concretely,":[96],"representation":[102],"(BPDR)":[103],"approach,":[104],"disentangles":[106],"into":[110],"multiple":[111],"bands":[113],"employs":[115],"non-shared":[116],"frequency-enhanced":[117],"multilayer":[118],"perceptrons":[119],"(MLPs)":[120],"each":[123],"band":[124],"independently.":[125],"We":[126],"prove":[127],"that":[128,185],"our":[129,186],"BPDR":[130],"ensures":[132],"effective":[133],"learning":[135,203],"by":[139],"demonstrating":[140,198],"its":[141,173],"global":[143],"convolution":[144],"property.":[145],"Besides,":[146],"design":[148],"Harmonic":[151],"(HR)":[153],"sets":[159],"continuously":[161],"track":[162],"comparisons":[163],"between":[164],"real":[165],"virtual":[167],"candidates,":[168],"where":[169],"theoretically":[171],"guarantee":[172],"ability":[174],"alleviate":[176],"Extensive":[181],"experimental":[182],"results":[183],"show":[184],"BandRank":[187],"achieves":[188],"average":[190],"improvement":[191],"of":[192],"21.31%":[193],"against":[194],"eight":[195],"baselines":[196],"while":[197],"superior":[199],"robustness":[200],"across":[201],"different":[202],"scenarios.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":6}],"updated_date":"2026-08-23T07:36:19.812096","created_date":"2025-10-10T00:00:00"}