{"id":"https://openalex.org/W2741530523","doi":"https://doi.org/10.1145/3077136.3082066","title":"Candidate Selection for Large Scale Personalized Search and Recommender Systems","display_name":"Candidate Selection for Large Scale Personalized Search and Recommender Systems","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2741530523","doi":"https://doi.org/10.1145/3077136.3082066","mag":"2741530523"},"language":"en","primary_location":{"id":"doi:10.1145/3077136.3082066","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3077136.3082066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-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/A5025883250","display_name":"Dhruv Arya","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":"Dhruv Arya","raw_affiliation_strings":["LinkedIn Corporation, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101577886","display_name":"Ganesh Venkataraman","orcid":"https://orcid.org/0009-0005-4007-8309"},"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":"Ganesh Venkataraman","raw_affiliation_strings":["LinkedIn Corporation, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022334611","display_name":"Aman Grover","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":"Aman Grover","raw_affiliation_strings":["LinkedIn Corporation, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002843568","display_name":"Krishnaram Kenthapadi","orcid":"https://orcid.org/0000-0003-1237-087X"},"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":"Krishnaram Kenthapadi","raw_affiliation_strings":["LinkedIn Corporation, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5025883250"],"corresponding_institution_ids":["https://openalex.org/I1316064682"],"apc_list":null,"apc_paid":null,"fwci":1.4509,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.86817899,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1391","last_page":"1393"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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/T11106","display_name":"Data Management and Algorithms","score":0.9979000091552734,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8597630262374878},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7816110849380493},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6946587562561035},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6903073191642761},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6290289163589478},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5756974816322327},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5304555296897888},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.49490970373153687},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.43478119373321533},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.4238939583301544},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.421907901763916},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3741036057472229},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.350117564201355},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3215883672237396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2672632336616516},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.18356174230575562}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8597630262374878},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7816110849380493},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6946587562561035},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6903073191642761},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6290289163589478},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5756974816322327},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5304555296897888},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.49490970373153687},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.43478119373321533},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.4238939583301544},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.421907901763916},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3741036057472229},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.350117564201355},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3215883672237396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2672632336616516},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.18356174230575562},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3077136.3082066","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3077136.3082066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1551408939","https://openalex.org/W2066636486","https://openalex.org/W2112941141","https://openalex.org/W2135050452","https://openalex.org/W2138909795","https://openalex.org/W2154610494","https://openalex.org/W2512971201","https://openalex.org/W2515120505","https://openalex.org/W2584969977"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W2247121321","https://openalex.org/W2391926582","https://openalex.org/W2087391438","https://openalex.org/W1966831329","https://openalex.org/W2316074893","https://openalex.org/W2020188645","https://openalex.org/W2739923608"],"abstract_inverted_index":{"Modern":[0],"day":[1],"social":[2,124],"media":[3,125],"search":[4,20],"and":[5,17,29,36,56,77,114,148,157],"recommender":[6],"systems":[7,25,46],"require":[8],"complex":[9],"query":[10,35],"formulation":[11],"that":[12],"incorporates":[13],"both":[14],"user":[15],"context":[16],"their":[18,34],"explicit":[19],"queries.":[21],"Users":[22],"expect":[23],"these":[24,45,139],"to":[26,33,42,52,62,68,82,92,151],"be":[27,83],"fast":[28],"provide":[30,57,132],"relevant":[31,60,80,100],"results":[32,55],"context.":[37],"With":[38],"millions":[39],"of":[40],"documents":[41,73],"choose":[43],"from,":[44],"utilize":[47],"a":[48,79,121,144],"multi-pass":[49],"scoring":[50,87],"function":[51],"narrow":[53,93],"the":[54,58,72,75,95,128,153],"most":[59],"ones":[61,101],"users.":[63],"Candidate":[64],"selection":[65,112,141],"is":[66],"required":[67],"sift":[69],"through":[70],"all":[71],"in":[74,102],"index":[76],"select":[78],"few":[81],"ranked":[84],"by":[85],"subsequent":[86],"functions.":[88],"It":[89],"becomes":[90],"crucial":[91],"down":[94],"document":[96],"set":[97],"while":[98],"maintaining":[99],"resulting":[103],"set.":[104],"In":[105,127],"this":[106],"tutorial":[107,134],"we":[108,131,136],"survey":[109],"various":[110],"candidate":[111,140],"techniques":[113],"deep":[115],"dive":[116],"into":[117],"case":[118],"studies":[119],"on":[120,143],"large":[122],"scale":[123],"platform.":[126],"later":[129],"half":[130],"hands-on":[133],"where":[135],"explore":[137],"building":[138],"models":[142],"real":[145],"world":[146],"dataset":[147],"see":[149],"how":[150],"balance":[152],"tradeoff":[154],"between":[155],"relevance":[156],"latency.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}