{"id":"https://openalex.org/W2515483217","doi":"https://doi.org/10.1145/2939672.2939718","title":"CaSMoS","display_name":"CaSMoS","publication_year":2016,"publication_date":"2016-08-08","ids":{"openalex":"https://openalex.org/W2515483217","doi":"https://doi.org/10.1145/2939672.2939718","mag":"2515483217"},"language":"en","primary_location":{"id":"doi:10.1145/2939672.2939718","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","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/A5079826085","display_name":"Fedor Borisyuk","orcid":"https://orcid.org/0009-0005-8171-7656"},"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":"Fedor Borisyuk","raw_affiliation_strings":["LinkedIn Corporation, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","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, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090191433","display_name":"David Stein","orcid":"https://orcid.org/0000-0001-9205-6471"},"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":"David Stein","raw_affiliation_strings":["LinkedIn Corporation, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055778766","display_name":"Bo Zhao","orcid":"https://orcid.org/0000-0002-3799-9183"},"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":"Bo Zhao","raw_affiliation_strings":["LinkedIn Corporation, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079826085"],"corresponding_institution_ids":["https://openalex.org/I1316064682"],"apc_list":null,"apc_paid":null,"fwci":3.0262,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.92366321,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"441","last_page":"450"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9983000159263611,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9962999820709229,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9939000010490417,"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/computer-science","display_name":"Computer science","score":0.8788784742355347},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7214376330375671},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5624290704727173},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5470014214515686},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.5245485901832581},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5050938725471497},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.475635290145874},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.4743833839893341},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.44067516922950745},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4253007769584656},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22554218769073486},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.19508129358291626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8788784742355347},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7214376330375671},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5624290704727173},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5470014214515686},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.5245485901832581},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5050938725471497},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.475635290145874},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.4743833839893341},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.44067516922950745},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4253007769584656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22554218769073486},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.19508129358291626},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2939672.2939718","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1551408939","https://openalex.org/W1560147776","https://openalex.org/W1574457532","https://openalex.org/W1991271936","https://openalex.org/W1994915827","https://openalex.org/W2025016813","https://openalex.org/W2039965491","https://openalex.org/W2080770071","https://openalex.org/W2080957047","https://openalex.org/W2091379987","https://openalex.org/W2111116800","https://openalex.org/W2114196190","https://openalex.org/W2131840460","https://openalex.org/W2154610494","https://openalex.org/W2397525010","https://openalex.org/W4211124088","https://openalex.org/W6670650750"],"related_works":["https://openalex.org/W2533706070","https://openalex.org/W2184474188","https://openalex.org/W3094024929","https://openalex.org/W2066869521","https://openalex.org/W2105258824","https://openalex.org/W3210975432","https://openalex.org/W2547614144","https://openalex.org/W2136530748","https://openalex.org/W2321599862","https://openalex.org/W1970380778"],"abstract_inverted_index":{"User":[0],"experience":[1],"at":[2],"social":[3],"media":[4],"and":[5,17,27,64,95,130,174,198,201],"web":[6],"platforms":[7],"such":[8,23,47],"as":[9,24,163,216],"LinkedIn":[10],"is":[11,91,124],"heavily":[12],"dependent":[13],"on":[14],"the":[15,49,52,55,101,140,144,166,203,206,235,238,243],"performance":[16],"scalability":[18,204],"of":[19,32,34,54,71,73,78,117,139,165,205,213,218,237],"its":[20],"products.":[21],"Applications":[22],"personalized":[25],"search":[26,60,187],"recommendations":[28],"require":[29],"real-time":[30],"scoring":[31,248],"millions":[33],"structured":[35],"candidate":[36,82,111,168,208],"documents":[37,99,129,132],"associated":[38],"with":[39,42,193],"each":[40],"query,":[41],"strict":[43],"latency":[44,229],"constraints.":[45],"In":[46],"applications,":[48],"query":[50],"incorporates":[51],"context":[53],"user":[56],"(in":[57],"addition":[58],"to":[59,86,93,126,136,153,178,231],"keywords":[61],"if":[62],"present),":[63],"hence":[65],"can":[66],"become":[67],"very":[68],"large,":[69],"comprising":[70],"thousands":[72],"Boolean":[74],"clauses":[75],"over":[76],"hundreds":[77],"document":[79],"attributes.":[80],"Consequently,":[81],"selection":[83,112,151,169,209],"techniques":[84],"need":[85],"be":[87,137,179],"applied":[88],"since":[89],"it":[90],"infeasible":[92],"retrieve":[94,131],"score":[96],"all":[97],"matching":[98],"from":[100],"underlying":[102],"inverted":[103],"index.":[104],"We":[105,146,171,189],"propose":[106],"CaSMoS,":[107],"a":[108,148],"machine":[109],"learned":[110],"framework":[113,123],"that":[114,133,160],"makes":[115],"use":[116],"Weighted":[118],"AND":[119],"(WAND)":[120],"query.":[121,145,170],"Our":[122,211],"designed":[125],"prune":[127],"irrelevant":[128],"are":[134,161],"likely":[135],"part":[138,164,217],"top-k":[141],"results":[142],"for":[143,157,245],"apply":[147],"constrained":[149],"feature":[150,158],"algorithm":[152],"learn":[154],"positive":[155],"weights":[156],"combinations":[159],"used":[162],"weighted":[167],"have":[172],"implemented":[173],"deployed":[175],"this":[176,214],"system":[177,215],"executed":[180],"in":[181,225,228],"real":[182],"time":[183],"using":[184],"LinkedIn's":[185,219],"Galene":[186],"platform.":[188],"perform":[190],"extensive":[191],"evaluation":[192],"different":[194],"training":[195],"data":[196],"approaches":[197],"parameter":[199],"settings,":[200],"investigate":[202],"proposed":[207],"model.":[210],"deployment":[212],"job":[220],"recommendation":[221],"engine":[222],"has":[223],"resulted":[224],"significant":[226],"reduction":[227],"(up":[230],"25%)":[232],"without":[233],"sacrificing":[234],"quality":[236],"retrieved":[239],"results,":[240],"thereby":[241],"paving":[242],"way":[244],"more":[246],"sophisticated":[247],"models.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-09-16T00:00:00"}