{"id":"https://openalex.org/W4224314868","doi":"https://doi.org/10.1145/3485447.3512108","title":"FIRE: Fast Incremental Recommendation with Graph Signal Processing","display_name":"FIRE: Fast Incremental Recommendation with Graph Signal Processing","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224314868","doi":"https://doi.org/10.1145/3485447.3512108"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3512108","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512108","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","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, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, 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, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, 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":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hansu Gu","raw_affiliation_strings":["Independent, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Independent, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100347854","display_name":"Jiahao Liu","orcid":"https://orcid.org/0000-0002-7777-312X"},"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":"Jiahao Liu","raw_affiliation_strings":["Fudan University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"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, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, 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, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2360","last_page":"2369"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9972000122070312,"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/T11478","display_name":"Caching and Content Delivery","score":0.972599983215332,"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":0.856021523475647},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6236656904220581},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.584417998790741},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5405361652374268},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5395210981369019},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.513149082660675},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45682293176651},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3950863182544708},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38317641615867615},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3658621609210968},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2076239287853241}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.856021523475647},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6236656904220581},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.584417998790741},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5405361652374268},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5395210981369019},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.513149082660675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45682293176651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3950863182544708},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38317641615867615},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3658621609210968},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2076239287853241},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3485447.3512108","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512108","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1720514416","https://openalex.org/W2054141820","https://openalex.org/W2108920354","https://openalex.org/W2475334473","https://openalex.org/W2583674722","https://openalex.org/W2605350416","https://openalex.org/W2733852074","https://openalex.org/W2912083425","https://openalex.org/W2914721378","https://openalex.org/W2945827377","https://openalex.org/W2945827670","https://openalex.org/W2963272802","https://openalex.org/W2963323306","https://openalex.org/W2964636989","https://openalex.org/W2965209830","https://openalex.org/W2965683718","https://openalex.org/W2972774416","https://openalex.org/W2990583386","https://openalex.org/W3045200674","https://openalex.org/W3100278010","https://openalex.org/W3101553402","https://openalex.org/W3176301896","https://openalex.org/W3210138510","https://openalex.org/W3211009588","https://openalex.org/W4232980324","https://openalex.org/W4300175872"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2103419012","https://openalex.org/W4390273403","https://openalex.org/W2988126442","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405"],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"are":[2,38,49],"incremental":[3,9,66,164],"in":[4,8,88,114],"nature.":[5],"Recent":[6],"progresses":[7],"recommendation":[10,67,165],"rely":[11],"on":[12,135],"capturing":[13],"the":[14,32,64,84,94,119,126,144,152,162],"temporal":[15,20,104,120],"dynamics":[16,121],"of":[17,96,122],"users/items":[18,54,123],"from":[19,70,83],"interaction":[21],"graphs,":[22],"so":[23],"that":[24,140],"their":[25],"user/item":[26,103],"embeddings":[27],"can":[28,117,142],"evolve":[29],"together":[30],"with":[31,40,161],"graph":[33,72,112],"structures.":[34],"However,":[35],"these":[36],"methods":[37],"faced":[39],"two":[41],"key":[42],"challenges:":[43],"1)":[44],"model":[45,97,153],"training":[46],"and/or":[47],"updating":[48,154],"time-consuming":[50,85],"and":[51,106,124,150],"2)":[52],"new":[53,111,130],"cannot":[55],"be":[56],"effectively":[57],"handled.":[58],"To":[59],"this":[60],"end,":[61],"we":[62,101],"propose":[63],"fast":[65],"(FIRE)":[68],"method":[69],"a":[71,147],"signal":[73],"processing":[74],"perspective.":[75],"FIRE":[76,141],"is":[77,169],"non-parametric":[78],"which":[79,116],"does":[80],"not":[81],"suffer":[82],"back-propagations":[86],"as":[87],"previous":[89],"learning-based":[90],"methods,":[91],"significantly":[92],"improving":[93],"efficiency":[95,155],"updating.":[98],"In":[99],"addition,":[100],"encode":[102],"information":[105,108],"side":[107],"by":[109,146,156],"designing":[110],"filters":[113],"FIRE,":[115],"capture":[118],"address":[125],"cold-start":[127],"issue":[128],"for":[129],"users/items,":[131],"respectively.":[132],"Experimental":[133],"studies":[134],"four":[136],"popular":[137],"datasets":[138],"demonstrate":[139],"improve":[143,151],"accuracy":[145],"large":[148],"margin":[149],"at":[157,171],"least":[158],"3X":[159],"compared":[160],"state-of-the-art":[163],"algorithms.":[166],"The":[167],"Code":[168],"available":[170],"https://github.com/Yaveng/FIRE.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}