{"id":"https://openalex.org/W1993415541","doi":"https://doi.org/10.1145/2009916.2010051","title":"Recommending ephemeral items at web scale","display_name":"Recommending ephemeral items at web scale","publication_year":2011,"publication_date":"2011-07-24","ids":{"openalex":"https://openalex.org/W1993415541","doi":"https://doi.org/10.1145/2009916.2010051","mag":"1993415541"},"language":"en","primary_location":{"id":"doi:10.1145/2009916.2010051","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2009916.2010051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","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/A5100359105","display_name":"Ye Chen","orcid":"https://orcid.org/0000-0002-4541-5918"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ye Chen","raw_affiliation_strings":["Microsoft Corporation, Mountain View, CA, USA","Microsoft Corporation, Mountain View, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft Corporation, Mountain View, CA, USA#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089723214","display_name":"John Canny","orcid":"https://orcid.org/0000-0002-7161-7927"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John F. Canny","raw_affiliation_strings":["University of California, Berkeley, Berkeley, CA, USA","University of California, Berkeley, Berkeley, CA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"University of California, Berkeley, Berkeley, CA USA","institution_ids":["https://openalex.org/I95457486"]}]}],"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":27,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1013","last_page":"1022"},"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7291831970214844},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6319445967674255},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.5657509565353394},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5354127883911133},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.45053714513778687},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4404025077819824},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4403691291809082},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4258696436882019},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.41979917883872986},{"id":"https://openalex.org/keywords/latent-class-model","display_name":"Latent class model","score":0.4167287349700928},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41142675280570984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32113951444625854},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.2101384699344635},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15963700413703918}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7291831970214844},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6319445967674255},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.5657509565353394},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5354127883911133},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.45053714513778687},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4404025077819824},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4403691291809082},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4258696436882019},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.41979917883872986},{"id":"https://openalex.org/C70727504","wikidata":"https://www.wikidata.org/wiki/Q1806878","display_name":"Latent class model","level":2,"score":0.4167287349700928},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41142675280570984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32113951444625854},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2101384699344635},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15963700413703918}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2009916.2010051","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2009916.2010051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W181283514","https://openalex.org/W398859631","https://openalex.org/W936106958","https://openalex.org/W949738197","https://openalex.org/W1550206324","https://openalex.org/W1597533204","https://openalex.org/W1718512272","https://openalex.org/W1880262756","https://openalex.org/W1974413746","https://openalex.org/W1982854196","https://openalex.org/W1992549066","https://openalex.org/W1994389483","https://openalex.org/W2054553473","https://openalex.org/W2060204748","https://openalex.org/W2080320419","https://openalex.org/W2084848593","https://openalex.org/W2097089247","https://openalex.org/W2097533650","https://openalex.org/W2099213975","https://openalex.org/W2106630408","https://openalex.org/W2107743791","https://openalex.org/W2135505871","https://openalex.org/W2136542423","https://openalex.org/W2170304975","https://openalex.org/W2341535507","https://openalex.org/W2606211438","https://openalex.org/W2626914210","https://openalex.org/W4205687621","https://openalex.org/W4233135949","https://openalex.org/W4240913316","https://openalex.org/W6637618339","https://openalex.org/W6674754770","https://openalex.org/W6684863674","https://openalex.org/W7014191107"],"related_works":["https://openalex.org/W1603253275","https://openalex.org/W1501016332","https://openalex.org/W4230230730","https://openalex.org/W1535265092","https://openalex.org/W4237379778","https://openalex.org/W2363394205","https://openalex.org/W1471855","https://openalex.org/W4381250654","https://openalex.org/W2103023456","https://openalex.org/W2031588620"],"abstract_inverted_index":{"We":[0,30,202,264],"describe":[1],"an":[2],"innovative":[3],"and":[4,42,65,172,194,208,224,247],"scalable":[5],"recommendation":[6,209,256,276],"system":[7,234,243],"successfully":[8],"deployed":[9],"at":[10,262],"eBay.":[11,263],"To":[12],"build":[13],"recommenders":[14],"for":[15,37,91,135,275],"long-tail":[16],"marketplaces":[17],"requires":[18],"projection":[19],"of":[20,27,39,63,78,94,110,113,123,160,182,221,260],"volatile":[21],"items":[22,50,114,261],"into":[23,165],"a":[24,33,61,70,76,117,156,183,270],"persistent":[25],"space":[26,122],"latent":[28,54,71,124,147,205],"products.":[29,55],"first":[31],"present":[32],"generative":[34,118],"clustering":[35,207],"model":[36],"collections":[38],"unstructured,":[40],"heterogeneous,":[41],"ephemeral":[43],"item":[44,57,185],"data,":[45],"under":[46,115],"the":[47,102,108,121,173,178,191,195,204,229,240,278],"assumption":[48],"that":[49,266],"are":[51,85,143],"generated":[52],"from":[53,137,149,216],"An":[56],"is":[58,73,99],"represented":[59],"as":[60,75,87,200],"vector":[62,77],"independently":[64],"distinctly":[66],"distributed":[67],"variables,":[68],"while":[69],"product":[72,169,206],"characterized":[74],"probability":[79,83],"distributions,":[80],"respectively.":[81],"The":[82,96],"distributions":[84],"chosen":[86],"natural":[88],"stochastic":[89],"models":[90,211],"different":[92],"types":[93],"data.":[95,140,284],"learning":[97],"objective":[98],"to":[100],"maximize":[101,190],"total":[103],"intra-cluster":[104],"coherence":[105],"measured":[106],"by":[107,145],"sum":[109],"log":[111],"likelihoods":[112],"such":[116],"process.":[119],"In":[120,152,228],"products,":[125],"robust":[126],"recommendations":[127,142],"can":[128,188],"then":[129],"be":[130],"derived":[131],"using":[132,212],"naive":[133],"Bayes":[134],"ranking,":[136],"historical":[138],"transactional":[139],"Item-based":[141],"achieved":[144],"inferring":[146],"products":[148],"unseen":[150],"items.":[151],"particular,":[153],"we":[154],"develop":[155],"probabilistic":[157,180],"scoring":[158],"function":[159],"recommended":[161],"items,":[162],"which":[163],"takes":[164],"account":[166],"item-product":[167],"membership,":[168],"purchase":[170],"probability,":[171],"important":[174],"auction-end-time":[175],"factor.":[176],"With":[177],"holistic":[179],"measure":[181],"prospective":[184],"purchase,":[186],"one":[187],"further":[189],"expected":[192],"revenue":[193],"more":[196],"subjective":[197],"user":[198,282],"satisfaction":[199],"well.":[201],"evaluated":[203],"ranking":[210],"real-world":[213],"e-commerce":[214],"data":[215],"eBay,":[217],"in":[218,244,277],"both":[219],"forms":[220],"offline":[222],"simulation":[223],"online":[225],"A/B":[226],"testing.":[227],"recent":[230],"production":[231,242],"launch,":[232],"our":[233],"yielded":[235],"3-5":[236],"folds":[237],"improvement":[238],"over":[239],"existing":[241],"click-through,":[245],"purchase-through":[246],"gross":[248],"merchandising":[249],"value;":[250],"thus":[251],"now":[252],"driving":[253],"100%":[254],"related":[255],"traffic":[257],"with":[258,280],"billions":[259],"believe":[265],"this":[267],"work":[268],"provides":[269],"practical":[271],"yet":[272],"principled":[273],"framework":[274],"domains":[279],"affluent":[281],"self-input":[283]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}