{"id":"https://openalex.org/W3080781457","doi":"https://doi.org/10.1145/3394486.3403262","title":"On Sampling Top-K Recommendation Evaluation","display_name":"On Sampling Top-K Recommendation Evaluation","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3080781457","doi":"https://doi.org/10.1145/3394486.3403262","mag":"3080781457"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403262","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2106.10621","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100407418","display_name":"Dong Li","orcid":"https://orcid.org/0000-0002-2599-6065"},"institutions":[{"id":"https://openalex.org/I149910238","display_name":"Kent State University","ror":"https://ror.org/049pfb863","country_code":"US","type":"education","lineage":["https://openalex.org/I149910238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dong Li","raw_affiliation_strings":["Kent State University, Kent, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kent State University, Kent, OH, USA","institution_ids":["https://openalex.org/I149910238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103270436","display_name":"Ruoming Jin","orcid":"https://orcid.org/0000-0003-1895-4243"},"institutions":[{"id":"https://openalex.org/I149910238","display_name":"Kent State University","ror":"https://ror.org/049pfb863","country_code":"US","type":"education","lineage":["https://openalex.org/I149910238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruoming Jin","raw_affiliation_strings":["Kent State University, Kent, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kent State University, Kent, OH, USA","institution_ids":["https://openalex.org/I149910238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101864158","display_name":"Jing Gao","orcid":"https://orcid.org/0009-0002-4502-5650"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing Gao","raw_affiliation_strings":["iLambda, Aurora, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"iLambda, Aurora, OH, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100382285","display_name":"Zhi Liu","orcid":"https://orcid.org/0000-0002-5248-4807"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhi Liu","raw_affiliation_strings":["iLambda, Aurora, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"iLambda, Aurora, OH, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100407418"],"corresponding_institution_ids":["https://openalex.org/I149910238"],"apc_list":null,"apc_paid":null,"fwci":6.4023,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.9676241,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2114","last_page":"2124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9968000054359436,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7097164988517761},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6539843678474426},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6306902170181274},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.4822888672351837},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4799661636352539},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.464655339717865},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43252986669540405},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.34687742590904236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33120638132095337},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2682313919067383},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.09944680333137512},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08495768904685974},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07332572340965271}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7097164988517761},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6539843678474426},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6306902170181274},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.4822888672351837},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4799661636352539},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.464655339717865},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43252986669540405},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.34687742590904236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33120638132095337},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2682313919067383},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.09944680333137512},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08495768904685974},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07332572340965271},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3394486.3403262","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2106.10621","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.10621","pdf_url":"https://arxiv.org/pdf/2106.10621","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2106.10621","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.10621","pdf_url":"https://arxiv.org/pdf/2106.10621","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1994389483","https://openalex.org/W2072271719","https://openalex.org/W2101409192","https://openalex.org/W2114079787","https://openalex.org/W2142144955","https://openalex.org/W2150886314","https://openalex.org/W2565948352","https://openalex.org/W2605350416","https://openalex.org/W2739273093","https://openalex.org/W2783603395","https://openalex.org/W2798972759","https://openalex.org/W2884134047","https://openalex.org/W2892888989","https://openalex.org/W2912745432","https://openalex.org/W2944441143","https://openalex.org/W2951707557","https://openalex.org/W2957191877","https://openalex.org/W2963085847","https://openalex.org/W2963714345","https://openalex.org/W2966349618","https://openalex.org/W2993053728","https://openalex.org/W3100278010","https://openalex.org/W3105114834","https://openalex.org/W3122507327","https://openalex.org/W4288083766","https://openalex.org/W4297790600"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2118758177","https://openalex.org/W4330338194","https://openalex.org/W2153520307","https://openalex.org/W2611989081","https://openalex.org/W2151459719","https://openalex.org/W623261610","https://openalex.org/W2316630966","https://openalex.org/W1976696937","https://openalex.org/W2059453987"],"abstract_inverted_index":{"Recently,":[0],"Rendle":[1],"has":[2],"warned":[3],"that":[4,85,96],"the":[5,42,45,65,97,114],"use":[6],"of":[7,18,67,105],"sampling-based":[8],"top-k":[9,70,99],"metrics":[10],"might":[11],"not":[12],"suffice.":[13],"This":[14],"throws":[15],"a":[16,32,80],"number":[17],"recent":[19],"studies":[20],"on":[21],"deep":[22],"learning-based":[23],"recommendation":[24],"algorithms,":[25],"and":[26,47,58,73,94,110],"classic":[27],"non-deep-learning":[28],"algorithms":[29],"using":[30],"such":[31],"metric,":[33],"into":[34],"jeopardy.":[35],"In":[36],"this":[37],"work,":[38],"we":[39,90],"thoroughly":[40],"investigate":[41],"relationship":[43],"between":[44],"sampling":[46,69,98],"global":[48,74,107,124],"top-K":[49,75],"Hit-Ratio":[50,100],"(HR,":[51],"or":[52],"Recall),":[53],"originally":[54],"proposed":[55],"by":[56,61,121],"Koren[2]":[57],"extensively":[59],"used":[60],"others.":[62],"By":[63],"formulating":[64],"problem":[66],"aligning":[68],"([email":[71,76],"protected]$)":[72],"protected])":[77],"Hit-Ratios":[78],"through":[79],"mapping":[81],"function":[82],"f,":[83],"so":[84],"[email":[86,88],"protected]~":[87],"protected](k),":[89],"demonstrate":[91],"both":[92],"theoretically":[93],"experimentally":[95],"provides":[101],"an":[102],"accurate":[103],"approximation":[104],"its":[106],"(exact)":[108],"counterpart,":[109],"can":[111],"consistently":[112],"predict":[113],"correct":[115],"winners":[116],"(the":[117],"same":[118],"as":[119],"indicate":[120],"their":[122],"corresponding":[123],"Hit-Ratios).":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":8}],"updated_date":"2026-04-26T08:31:28.666265","created_date":"2025-10-10T00:00:00"}
