{"id":"https://openalex.org/W2972428112","doi":"https://doi.org/10.1145/3298689.3347032","title":"Predicting online performance of job recommender systems with offline evaluation","display_name":"Predicting online performance of job recommender systems with offline evaluation","publication_year":2019,"publication_date":"2019-09-10","ids":{"openalex":"https://openalex.org/W2972428112","doi":"https://doi.org/10.1145/3298689.3347032","mag":"2972428112"},"language":"en","primary_location":{"id":"doi:10.1145/3298689.3347032","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3298689.3347032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th ACM Conference on Recommender Systems","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/A5030142025","display_name":"Adrien Mogenet","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adrien Mogenet","raw_affiliation_strings":["Indeed, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indeed, Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006222293","display_name":"Tuan Anh Pham","orcid":"https://orcid.org/0000-0003-0025-7263"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tuan Anh Nguyen Pham","raw_affiliation_strings":["Indeed, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indeed, Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015670174","display_name":"Masahiro Kazama","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Masahiro Kazama","raw_affiliation_strings":["Indeed, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indeed, Tokyo, Japan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036642666","display_name":"Jialin Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jialin Kong","raw_affiliation_strings":["Indeed, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indeed, Tokyo, Japan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3527,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.69434332,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"477","last_page":"480"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.8713094592094421},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7740354537963867},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.680412769317627},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6683633923530579},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6219519972801208},{"id":"https://openalex.org/keywords/online-and-offline","display_name":"Online and offline","score":0.5516404509544373},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5001153945922852},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.44439804553985596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38116851449012756},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33145672082901},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.326332688331604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8713094592094421},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7740354537963867},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.680412769317627},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6683633923530579},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6219519972801208},{"id":"https://openalex.org/C2780102126","wikidata":"https://www.wikidata.org/wiki/Q10928179","display_name":"Online and offline","level":2,"score":0.5516404509544373},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5001153945922852},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.44439804553985596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38116851449012756},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33145672082901},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.326332688331604},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3298689.3347032","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3298689.3347032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W53982325","https://openalex.org/W1531237901","https://openalex.org/W1971040550","https://openalex.org/W2010953147","https://openalex.org/W2012903477","https://openalex.org/W2049670925","https://openalex.org/W2118934678","https://openalex.org/W2150886314","https://openalex.org/W2573253449","https://openalex.org/W2585469747","https://openalex.org/W2808787330","https://openalex.org/W2963061618","https://openalex.org/W4292078479"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W3125580266","https://openalex.org/W44246808","https://openalex.org/W4317039510","https://openalex.org/W4238861846","https://openalex.org/W790944756"],"abstract_inverted_index":{"At":[0],"Indeed,":[1],"recommender":[2],"systems":[3],"are":[4,20],"used":[5],"to":[6,40,65,74,114,124],"recommend":[7],"jobs.":[8],"In":[9,53,81],"this":[10,82],"context,":[11],"implicit":[12],"and":[13,89,103],"explicit":[14],"feedback":[15],"signals":[16],"we":[17,84,96,101],"can":[18,121],"collect":[19],"rare":[21],"events,":[22],"making":[23],"the":[24,36,42,55,86,98,106,126],"task":[25],"of":[26,92],"evaluation":[27,31,57,99,119],"more":[28],"complex.":[29],"Online":[30],"(A/B":[32],"testing)":[33],"is":[34,49,59,63],"usually":[35],"most":[37],"reliable":[38,68],"way":[39],"measure":[41],"results":[43],"from":[44],"our":[45,72],"experiments,":[46],"but":[47,61],"it":[48,62,67,70],"a":[50],"slow":[51],"process.":[52],"contrast,":[54],"offline":[56,88,107,118],"process":[58,120],"faster,":[60],"critical":[64],"make":[66],"as":[69],"informs":[71],"decision":[73],"roll":[75],"out":[76],"new":[77],"improvements":[78],"in":[79],"production.":[80],"paper,":[83],"review":[85],"comparative":[87],"online":[90,112],"performances":[91],"three":[93],"recommendations":[94],"models,":[95],"describe":[97],"metrics":[100,109,113],"use":[102],"analyze":[104],"how":[105,116],"performance":[108],"correlate":[110],"with":[111],"understand":[115],"an":[117],"be":[122],"leveraged":[123],"inform":[125],"decisions.":[127]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
