{"id":"https://openalex.org/W4396722922","doi":"https://doi.org/10.1145/3589334.3645368","title":"Hierarchical Graph Signal Processing for Collaborative Filtering","display_name":"Hierarchical Graph Signal Processing for Collaborative Filtering","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4396722922","doi":"https://doi.org/10.1145/3589334.3645368"},"language":"en","primary_location":{"id":"doi:10.1145/3589334.3645368","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","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/A5059093140","display_name":"Jiafeng Xia","orcid":"https://orcid.org/0009-0000-6018-7725"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiafeng Xia","raw_affiliation_strings":["Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0000-6018-7725","affiliations":[{"raw_affiliation_string":"Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440920","display_name":"Dongsheng Li","orcid":"https://orcid.org/0000-0003-3103-8442"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongsheng Li","raw_affiliation_strings":["Microsoft Research Asia, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-3103-8442","affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Shanghai, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071156485","display_name":"Hansu Gu","orcid":"https://orcid.org/0000-0002-1426-3210"},"institutions":[{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hansu Gu","raw_affiliation_strings":["Independent Researcher, Seattle, USA"],"raw_orcid":"https://orcid.org/0000-0002-1426-3210","affiliations":[{"raw_affiliation_string":"Independent Researcher, Seattle, USA","institution_ids":["https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004237040","display_name":"Tun Lu","orcid":"https://orcid.org/0000-0002-6633-4826"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tun Lu","raw_affiliation_strings":["Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6633-4826","affiliations":[{"raw_affiliation_string":"Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364191","display_name":"Peng Zhang","orcid":"https://orcid.org/0000-0002-9109-4625"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9109-4625","affiliations":[{"raw_affiliation_string":"Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004722925","display_name":"Li Shang","orcid":"https://orcid.org/0000-0003-3944-7531"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Shang","raw_affiliation_strings":["Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-3944-7531","affiliations":[{"raw_affiliation_string":"Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091087409","display_name":"Ning Gu","orcid":"https://orcid.org/0000-0002-2915-974X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Gu","raw_affiliation_strings":["Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2915-974X","affiliations":[{"raw_affiliation_string":"Fudan University & School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3229","last_page":"3240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9631999731063843,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.7021605968475342},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.5737406611442566},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5020732879638672},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35798805952072144},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.18653401732444763},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.09646600484848022}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7021605968475342},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.5737406611442566},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5020732879638672},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35798805952072144},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.18653401732444763},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.09646600484848022}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589334.3645368","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3851921960","display_name":null,"funder_award_id":"62172106, 61932007, 62372113","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1985690171","https://openalex.org/W2013416056","https://openalex.org/W2042281163","https://openalex.org/W2055945388","https://openalex.org/W2095897464","https://openalex.org/W2129107602","https://openalex.org/W2194775991","https://openalex.org/W2766953000","https://openalex.org/W2796431263","https://openalex.org/W2807021761","https://openalex.org/W2945827670","https://openalex.org/W2998431760","https://openalex.org/W3044311607","https://openalex.org/W3045200674","https://openalex.org/W3046435230","https://openalex.org/W3094605801","https://openalex.org/W3100278010","https://openalex.org/W3100324210","https://openalex.org/W3100848837","https://openalex.org/W3153106544","https://openalex.org/W3153325943","https://openalex.org/W3156861396","https://openalex.org/W3176301896","https://openalex.org/W3209428314","https://openalex.org/W3210138510","https://openalex.org/W3211009588","https://openalex.org/W3211143493","https://openalex.org/W4212799635","https://openalex.org/W4220909642","https://openalex.org/W4224314868","https://openalex.org/W4241632258","https://openalex.org/W4306815981","https://openalex.org/W4319452302","https://openalex.org/W4327671700","https://openalex.org/W4384636842","https://openalex.org/W4387848554"],"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":{"Graph":[0],"Signal":[1],"Processing":[2],"(GSP)":[3],"has":[4],"proven":[5],"to":[6,107,132,137,163,186],"be":[7],"a":[8,67,130],"highly":[9],"effective":[10],"and":[11,47,121,167,189,197],"efficient":[12],"tool":[13],"for":[14,74],"predicting":[15],"user":[16,27,90,109,139,147,165,169],"future":[17,170],"interactions":[18,33,96,171],"in":[19,58,193],"recommender":[20],"systems.":[21],"However,":[22],"current":[23],"GSP":[24],"methods":[25,192],"recognize":[26,138,157],"interaction":[28,41,55,92,119,141,159],"patterns":[29,42,93,105,142],"based":[30],"on":[31,176],"the":[32,39,84,103,123,133,181],"of":[34,79,97,183,195],"all":[35,146],"users,":[36],"so":[37,161],"that":[38,88,127],"recognized":[40,104],"are":[43],"not":[44],"fully":[45],"user-matched":[46,158],"easily":[48],"impacted":[49],"by":[50,114],"other":[51,115,187],"users":[52,98,116],"with":[53,99,117],"different":[54,118],"behaviors,":[56,120],"resulting":[57],"sub-optimal":[59],"recommendation":[60,191],"performance.":[61],"To":[62],"this":[63],"end,":[64],"we":[65],"propose":[66],"hierarchical":[68],"graph":[69],"signal":[70],"processing":[71],"method":[72],"(HiGSP)":[73],"collaborative":[75],"filtering,":[76],"which":[77],"consists":[78],"two":[80,153],"key":[81],"modules:":[82],"1)":[83],"cluster-wise":[85,134],"filter":[86,125,135],"module":[87,126,136],"recognizes":[89],"unique":[91],"merely":[94],"from":[95,145],"similar":[100],"preferences,":[101],"making":[102],"able":[106],"reflect":[108],"preference":[110,166],"without":[111],"being":[112],"influenced":[113],"2)":[122],"globally-aware":[124],"serves":[128],"as":[129,162],"complementary":[131],"general":[140],"more":[143,172],"effectively":[144],"interactions.":[148],"By":[149],"linearly":[150],"combining":[151],"these":[152],"modules,":[154],"HiGSP":[155,184],"can":[156],"patterns,":[160],"model":[164],"predict":[168],"accurately.":[173],"Extensive":[174],"experiments":[175],"six":[177],"real-world":[178],"datasets":[179],"demonstrate":[180],"superiority":[182],"compared":[185],"GCN-based":[188],"GSP-based":[190],"terms":[194],"efficacy":[196],"efficiency.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}