{"id":"https://openalex.org/W4400228957","doi":"https://doi.org/10.1109/tkde.2024.3418080","title":"FPSR+: Toward Robust, Efficient, and Scalable Collaborative Filtering With Partition-Aware Item Similarity Modeling","display_name":"FPSR+: Toward Robust, Efficient, and Scalable Collaborative Filtering With Partition-Aware Item Similarity Modeling","publication_year":2024,"publication_date":"2024-07-02","ids":{"openalex":"https://openalex.org/W4400228957","doi":"https://doi.org/10.1109/tkde.2024.3418080"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2024.3418080","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tkde.2024.3418080","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","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/A5071769223","display_name":"Tianjun Wei","orcid":"https://orcid.org/0000-0001-7311-7101"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tianjun Wei","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7311-7101","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050716572","display_name":"Tommy W. S. Chow","orcid":"https://orcid.org/0000-0001-7051-0434"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tommy W. S. Chow","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7051-0434","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049838944","display_name":"Jianghong Ma","orcid":"https://orcid.org/0000-0002-0524-3584"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianghong Ma","raw_affiliation_strings":["Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-0524-3584","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6109,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.72495108,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"36","issue":"12","first_page":"8283","last_page":"8296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9193999767303467,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9193999767303467,"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":0.8408124446868896},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.6562074422836304},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6346282362937927},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6023690700531006},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6004320383071899},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.469943106174469},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3629218339920044},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.31256628036499023},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.2950892448425293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27499300241470337},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.19632285833358765},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08084976673126221}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8408124446868896},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.6562074422836304},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6346282362937927},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6023690700531006},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6004320383071899},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.469943106174469},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3629218339920044},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.31256628036499023},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.2950892448425293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27499300241470337},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.19632285833358765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08084976673126221},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2024.3418080","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tkde.2024.3418080","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1327405719","display_name":null,"funder_award_id":"62073272","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7502385493","display_name":null,"funder_award_id":"62202122","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8910824876","display_name":null,"funder_award_id":"2024A1515011949","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1977361006","https://openalex.org/W1979740015","https://openalex.org/W1987431925","https://openalex.org/W2017987256","https://openalex.org/W2042281163","https://openalex.org/W2051142108","https://openalex.org/W2054141820","https://openalex.org/W2055155379","https://openalex.org/W2095293504","https://openalex.org/W2097417531","https://openalex.org/W2121947440","https://openalex.org/W2140310134","https://openalex.org/W2142144955","https://openalex.org/W2217748804","https://openalex.org/W2511264801","https://openalex.org/W2605350416","https://openalex.org/W2912745432","https://openalex.org/W2945827670","https://openalex.org/W2949763225","https://openalex.org/W2952337488","https://openalex.org/W2955597675","https://openalex.org/W2963709987","https://openalex.org/W2998089494","https://openalex.org/W3012640652","https://openalex.org/W3014542904","https://openalex.org/W3045200674","https://openalex.org/W3084805822","https://openalex.org/W3100278010","https://openalex.org/W3101708421","https://openalex.org/W3106369320","https://openalex.org/W3156861396","https://openalex.org/W3176301896","https://openalex.org/W3176923454","https://openalex.org/W3211009588","https://openalex.org/W3211143493","https://openalex.org/W4212843742","https://openalex.org/W4220909642","https://openalex.org/W4280613708","https://openalex.org/W4284666445","https://openalex.org/W4292363360","https://openalex.org/W4320720392","https://openalex.org/W6637414576","https://openalex.org/W6640485552","https://openalex.org/W6786222671"],"related_works":["https://openalex.org/W3014393615","https://openalex.org/W131178872","https://openalex.org/W2389818373","https://openalex.org/W2796850053","https://openalex.org/W237510953","https://openalex.org/W2362248139","https://openalex.org/W2165888085","https://openalex.org/W2389600025","https://openalex.org/W2076210137","https://openalex.org/W2984080994"],"abstract_inverted_index":{"Collaborative":[0],"filtering":[1],"(CF)":[2],"has":[3],"been":[4],"extensively":[5],"studied":[6],"in":[7,83,142,158,191],"recommendation,":[8],"spawning":[9],"various":[10],"solutions.":[11],"While":[12],"graph":[13,98],"convolution":[14],"networks":[15],"(GCNs)":[16],"are":[17],"effective":[18],"at":[19],"representation":[20],"learning,":[21],"their":[22],"efficiency":[23],"is":[24],"lacking.":[25],"Comparatively,":[26],"item":[27,85,181],"similarity":[28,76,105,113,182],"model":[29,95],"efficiently":[30],"establishes":[31],"direct":[32],"relationships":[33],"between":[34],"items.":[35],"In":[36,56],"spite":[37],"of":[38,48,62,71,75,104,115,136,139,156,173],"this,":[39],"the":[40,46,63,69,73,79,84,102,137,154,159,170],"modeling":[41,77,106,114],"problem":[42],"grows":[43],"quadratically":[44],"as":[45,184,186],"number":[47],"items":[49,116,141],"increases.":[50],"This":[51],"poses":[52],"critical":[53],"scalability":[54],"issues.":[55],"this":[57],"paper,":[58],"through":[59],"an":[60,134],"investigation":[61],"latest":[64],"GCN":[65,178],"model,":[66],"we":[67,91,111,144],"reveal":[68],"feasibility":[70],"optimizing":[72],"process":[74],"using":[78],"underlying":[80],"group":[81],"structure":[82],"set.":[86],"Based":[87],"on":[88,165],"these":[89],"findings,":[90],"propose":[92,145],"a":[93,146],"novel":[94],"which":[96],"introduces":[97],"partitioning":[99],"to":[100,129],"reduce":[101],"scale":[103],"problem,":[107],"dubbed":[108],"FPSR+.":[109],"Specifically,":[110],"divide":[112],"into":[117],"sub-problems":[118],"within":[119],"each":[120],"partition,":[121],"and":[122,125,180,189],"incorporate":[123],"global":[124],"local":[126],"prior":[127],"knowledge":[128],"alleviate":[130],"information":[131],"loss.":[132],"Following":[133],"analysis":[135],"properties":[138],"different":[140],"partitioning,":[143],"new":[147],"hub":[148],"set":[149],"selection":[150],"strategy":[151],"that":[152],"improves":[153],"robustness":[155],"FPSR+":[157,174],"small":[160],"partition":[161],"case.":[162],"Extensive":[163],"experiments":[164],"four":[166],"real-world":[167],"datasets":[168],"demonstrate":[169],"superior":[171],"performance":[172],"compared":[175],"with":[176],"state-of-the-art":[177],"models":[179],"models,":[183],"well":[185],"several-fold":[187],"speedups":[188],"reductions":[190],"parameter":[192],"storage.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}