{"id":"https://openalex.org/W4320720392","doi":"https://doi.org/10.1145/3543507.3583240","title":"Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation","display_name":"Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4320720392","doi":"https://doi.org/10.1145/3543507.3583240"},"language":"en","primary_location":{"id":"doi:10.1145/3543507.3583240","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543507.3583240","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 2023","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholars.cityu.edu.hk/en/publications/fine-tuning-partition-aware-item-similarities-for-efficient-and-s","any_repository_has_fulltext":true},"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":["City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7311-7101","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","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":["Harbin Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-0524-3584","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","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":["City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7051-0434","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7185,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.86747559,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"823","last_page":"832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9952999949455261,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9952999949455261,"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":0.7573885917663574},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.7445643544197083},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.701452910900116},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.35993146896362305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3256916403770447},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.16046902537345886},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11506420373916626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7573885917663574},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.7445643544197083},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.701452910900116},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.35993146896362305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3256916403770447},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.16046902537345886},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11506420373916626},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3543507.3583240","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543507.3583240","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 2023","raw_type":"proceedings-article"},{"is_oa":true,"landing_page_url":"https://scholars.cityu.edu.hk/en/publications/fine-tuning-partition-aware-item-similarities-for-efficient-and-s","pdf_url":null,"source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wei, T, Ma, J & Chow, T W S 2023, Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation. in The ACM Web Conference 2023 : Proceedings of The World Wide Web Conference WWW 2023. Association for Computing Machinery, New York, NY, pp. 823-832, ACM Web Conference 2023 (WWW '23), Austin, Texas, United States, 30/04/23. https://doi.org/10.1145/3543507.3583240","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:publications/9091de78-a113-45a7-b6d6-77f19215a61d","is_oa":true,"landing_page_url":"https://hdl.handle.net/2031/9091de78-a113-45a7-b6d6-77f19215a61d","pdf_url":null,"source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wei, T, Ma, J & Chow, T W S 2023, Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation. in The ACM Web Conference 2023 : Proceedings of The World Wide Web Conference WWW 2023. Association for Computing Machinery, New York, NY, pp. 823-832, ACM Web Conference 2023 (WWW '23), Austin, Texas, United States, 30/04/23. https://doi.org/10.1145/3543507.3583240","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://scholars.cityu.edu.hk/en/publications/fine-tuning-partition-aware-item-similarities-for-efficient-and-s","pdf_url":null,"source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wei, T, Ma, J & Chow, T W S 2023, Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation. in The ACM Web Conference 2023 : Proceedings of The World Wide Web Conference WWW 2023. Association for Computing Machinery, New York, NY, pp. 823-832, ACM Web Conference 2023 (WWW '23), Austin, Texas, United States, 30/04/23. https://doi.org/10.1145/3543507.3583240","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G125593987","display_name":null,"funder_award_id":"CityU 11216620","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"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"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1977361006","https://openalex.org/W1987431925","https://openalex.org/W2042281163","https://openalex.org/W2051142108","https://openalex.org/W2054141820","https://openalex.org/W2055155379","https://openalex.org/W2095293504","https://openalex.org/W2121947440","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/W2952337488","https://openalex.org/W2963709987","https://openalex.org/W2964015378","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/W3100324210","https://openalex.org/W3101708421","https://openalex.org/W3106369320","https://openalex.org/W3156861396","https://openalex.org/W3176301896","https://openalex.org/W3176923454","https://openalex.org/W3208227120","https://openalex.org/W3211009588","https://openalex.org/W3211143493","https://openalex.org/W4212843742","https://openalex.org/W4220909642","https://openalex.org/W4284666445","https://openalex.org/W4292363360"],"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/W4401278057"],"abstract_inverted_index":{"Collaborative":[0],"filtering":[1],"(CF)":[2],"is":[3,137,145],"widely":[4],"searched":[5],"in":[6,20,64,67,85,99,139],"recommendation":[7],"with":[8,152,166,188,195],"various":[9],"types":[10],"of":[11,15,25,133],"solutions.":[12],"Recent":[13],"success":[14],"Graph":[16],"Convolution":[17],"Networks":[18],"(GCN)":[19],"CF":[21],"demonstrates":[22],"the":[23,59,80,94,100,119,130,134,167,181],"effectiveness":[24],"modeling":[26,69,122],"high-order":[27],"relationships":[28,50],"through":[29,51],"graphs,":[30],"while":[31],"repetitive":[32],"graph":[33,81,115,136],"convolution":[34],"and":[35,92,191],"iterative":[36],"batch":[37],"optimization":[38],"limit":[39],"their":[40,56],"efficiency.":[41],"Instead,":[42],"item":[43,61,96,110,120,150,192],"similarity":[44,68,111,121,193],"models":[45,187,194],"attempt":[46],"to":[47,117,147,164],"construct":[48],"direct":[49],"efficient":[52],"interaction":[53],"encoding.":[54],"Despite":[55],"great":[57],"performance,":[58],"growing":[60],"numbers":[62],"result":[63],"quadratic":[65],"growth":[66],"process,":[70],"posing":[71],"critical":[72],"scalability":[73],"problems.":[74],"In":[75],"this":[76],"paper,":[77],"we":[78,106,127],"investigate":[79],"sampling":[82],"strategy":[83,157],"adopted":[84],"latest":[86],"GCN":[87,186],"model":[88,112,183],"for":[89],"efficiency":[90],"improving,":[91],"identify":[93],"potential":[95],"group":[97],"structure":[98],"sampled":[101],"graph.":[102],"Based":[103],"on":[104,176],"this,":[105],"propose":[107],"a":[108,153],"novel":[109],"which":[113],"introduces":[114],"partitioning":[116],"restrict":[118],"within":[123],"each":[124],"partition.":[125],"Specifically,":[126],"show":[128,179],"that":[129,180],"spectral":[131],"information":[132,168],"original":[135],"well":[138],"preserving":[140],"global-level":[141],"information.":[142],"Then,":[143],"it":[144],"added":[146],"fine-tune":[148],"local":[149],"similarities":[151],"new":[154],"data":[155],"augmentation":[156],"acted":[158],"as":[159],"partition-aware":[160],"prior":[161],"knowledge,":[162],"jointly":[163],"cope":[165],"loss":[169],"brought":[170],"by":[171],"partitioning.":[172],"Experiments":[173],"carried":[174],"out":[175],"4":[177],"datasets":[178],"proposed":[182],"outperforms":[184],"state-of-the-art":[185],"10x":[189],"speed-up":[190],"95%":[196],"parameter":[197],"storage":[198],"savings.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-17T08:01:34.144755","created_date":"2025-10-10T00:00:00"}