{"id":"https://openalex.org/W4414035082","doi":"https://doi.org/10.1145/3705328.3748116","title":"Scaling Retrieval for Web-Scale Recommenders: Lessons from Inverted Indexes to Embedding Search","display_name":"Scaling Retrieval for Web-Scale Recommenders: Lessons from Inverted Indexes to Embedding Search","publication_year":2025,"publication_date":"2025-09-06","ids":{"openalex":"https://openalex.org/W4414035082","doi":"https://doi.org/10.1145/3705328.3748116"},"language":"en","primary_location":{"id":"doi:10.1145/3705328.3748116","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3705328.3748116","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3705328.3748116","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3705328.3748116","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084411084","display_name":"Yu-Chin Juan","orcid":null},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuchin Juan","raw_affiliation_strings":["LinkedIn, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0009-0006-0956-0575","affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103534562","display_name":"Jiacong Shen","orcid":"https://orcid.org/0009-0000-5258-6523"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianqiang Shen","raw_affiliation_strings":["LinkedIn, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0009-0000-5258-6523","affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081121323","display_name":"S. Zhang","orcid":"https://orcid.org/0009-0004-1725-416X"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaobo Zhang","raw_affiliation_strings":["LinkedIn, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0009-0004-1725-416X","affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013032251","display_name":"Qianqi Shen","orcid":"https://orcid.org/0000-0002-9323-6404"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qianqi Shen","raw_affiliation_strings":["LinkedIn, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-9323-6404","affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Caleb Johnson","orcid":"https://orcid.org/0009-0000-9735-3328"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Caleb Johnson","raw_affiliation_strings":["LinkedIn, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0009-0000-9735-3328","affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006012163","display_name":"Luke Simon","orcid":null},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luke Simon","raw_affiliation_strings":["LinkedIn, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0009-0004-4560-6361","affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004471013","display_name":"Liangjie Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liangjie Hong","raw_affiliation_strings":["LinkedIn, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0009-0000-4595-4631","affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wenjing Zhang","orcid":"https://orcid.org/0009-0000-6510-1222"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenjing Zhang","raw_affiliation_strings":["LinkedIn, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0009-0000-6510-1222","affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5084411084"],"corresponding_institution_ids":["https://openalex.org/I1316064682"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21661694,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1066","last_page":"1069"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T11106","display_name":"Data Management and Algorithms","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.7739925384521484},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6599372029304504},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6166046857833862},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5827011466026306},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5790554881095886},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4227685332298279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3004428744316101},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1773519217967987},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07728418707847595}],"concepts":[{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.7739925384521484},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6599372029304504},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6166046857833862},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5827011466026306},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5790554881095886},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4227685332298279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3004428744316101},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1773519217967987},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07728418707847595},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3705328.3748116","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3705328.3748116","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3705328.3748116","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3705328.3748116","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3705328.3748116","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3705328.3748116","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414035082.pdf","grobid_xml":"https://content.openalex.org/works/W4414035082.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W2112647999","https://openalex.org/W2124509324","https://openalex.org/W2340309946","https://openalex.org/W2515120505","https://openalex.org/W2515483217","https://openalex.org/W2746385174","https://openalex.org/W2963469388","https://openalex.org/W2972801466","https://openalex.org/W3036129238","https://openalex.org/W3036320503","https://openalex.org/W3093586140","https://openalex.org/W3098468692","https://openalex.org/W3098683167","https://openalex.org/W3166125679","https://openalex.org/W4372046852","https://openalex.org/W4403577447"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W141820298","https://openalex.org/W2037549926","https://openalex.org/W2049584446","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W2079781215","https://openalex.org/W4378770497","https://openalex.org/W4308245303","https://openalex.org/W2014033564"],"abstract_inverted_index":{"Web-scale":[0],"search":[1],"and":[2,13,49,67,80,106,115],"recommendation":[3],"systems":[4],"depend":[5],"on":[6],"efficient":[7],"retrieval":[8,24,39,76,98,129],"to":[9,35,74,94],"manage":[10],"massive":[11],"datasets":[12],"user":[14],"traffic.This":[15],"paper":[16],"chronicles":[17],"our":[18],"evolutionary":[19],"path":[20],"in":[21,65],"building":[22,126],"the":[23,111],"layer":[25],"at":[26,70],"LinkedIn,":[27],"progressing":[28],"from":[29],"a":[30,36,96],"CPU-based":[31],"inverted":[32],"index":[33],"system":[34,99],"GPU-accelerated":[37],"embedding-based":[38,75],"system.Initially":[40],"anchored":[41],"by":[42,54],"traditional":[43],"term-based":[44],"retrieval,":[45],"we":[46,72],"enhanced":[47],"relevance":[48],"productivity":[50],"through":[51],"learning-to-retrieve":[52],"approaches":[53],"generating":[55],"mappings":[56],"among":[57],"inferred":[58],"attributes.As":[59],"these":[60],"early":[61],"efforts":[62],"encountered":[63],"limitations":[64],"inferring":[66],"matching":[68],"attributes":[69],"scale,":[71],"transitioned":[73],"for":[77,101,125],"greater":[78],"flexibility":[79],"performance,":[81,103],"but":[82],"found":[83],"that":[84],"existing":[85],"infrastructure":[86,112],"couldn't":[87],"support":[88],"large-scale":[89],"production":[90],"needs.This":[91],"led":[92],"us":[93],"develop":[95],"GPUbased":[97],"designed":[100],"high":[102],"flexible":[104,128],"modeling,":[105],"multi-objective":[107],"business":[108],"optimization.We":[109],"present":[110],"innovations,":[113],"optimizations,":[114],"key":[116],"lessons":[117],"learned":[118],"throughout":[119],"this":[120],"transition,":[121],"offering":[122],"practical":[123],"insights":[124],"scalable,":[127],"systems.":[130]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
