{"id":"https://openalex.org/W2066289596","doi":"https://doi.org/10.1145/2414782.2414784","title":"Approximate Recall Confidence Intervals","display_name":"Approximate Recall Confidence Intervals","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2066289596","doi":"https://doi.org/10.1145/2414782.2414784","mag":"2066289596"},"language":"en","primary_location":{"id":"doi:10.1145/2414782.2414784","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2414782.2414784","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-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/A5110722281","display_name":"William Webber","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"William Webber","raw_affiliation_strings":["University of Maryland"],"affiliations":[{"raw_affiliation_string":"University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5110722281"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":2.37024683,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.90783858,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"31","issue":"1","first_page":"1","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9855999946594238,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9850000143051147,"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/confidence-interval","display_name":"Confidence interval","score":0.6008234620094299},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5854251980781555},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5818182826042175},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5808225274085999},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5570402145385742},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5525116324424744},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5068204998970032},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.37374234199523926},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35865068435668945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24076083302497864},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10703954100608826}],"concepts":[{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.6008234620094299},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5854251980781555},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5818182826042175},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5808225274085999},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5570402145385742},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5525116324424744},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5068204998970032},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.37374234199523926},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35865068435668945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24076083302497864},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10703954100608826},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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":2,"locations":[{"id":"doi:10.1145/2414782.2414784","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2414782.2414784","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.751.5705","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.751.5705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1202.2880.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","score":0.75,"id":"https://metadata.un.org/sdg/1"}],"awards":[{"id":"https://openalex.org/G2340282997","display_name":null,"funder_award_id":"1065250","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W31519287","https://openalex.org/W168394548","https://openalex.org/W1482736186","https://openalex.org/W1617959293","https://openalex.org/W1775260482","https://openalex.org/W1963842340","https://openalex.org/W1964488075","https://openalex.org/W1986439495","https://openalex.org/W1986480666","https://openalex.org/W1995139576","https://openalex.org/W1998321650","https://openalex.org/W2002302568","https://openalex.org/W2006681603","https://openalex.org/W2006818128","https://openalex.org/W2008535408","https://openalex.org/W2009954908","https://openalex.org/W2010211899","https://openalex.org/W2016310355","https://openalex.org/W2019922470","https://openalex.org/W2026437537","https://openalex.org/W2029685080","https://openalex.org/W2037571747","https://openalex.org/W2068495339","https://openalex.org/W2075893676","https://openalex.org/W2081983182","https://openalex.org/W2084568079","https://openalex.org/W2087511931","https://openalex.org/W2091397788","https://openalex.org/W2106578604","https://openalex.org/W2137591261","https://openalex.org/W2143707047","https://openalex.org/W2162445884","https://openalex.org/W2165244071","https://openalex.org/W2165266696","https://openalex.org/W2319777021","https://openalex.org/W2338257668","https://openalex.org/W2348336253","https://openalex.org/W2800198128","https://openalex.org/W4232383088","https://openalex.org/W4245600908","https://openalex.org/W4246592094","https://openalex.org/W4361868505","https://openalex.org/W6628747436","https://openalex.org/W6675993677"],"related_works":["https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W2140186469","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W4318559728","https://openalex.org/W2775233965","https://openalex.org/W4360995913","https://openalex.org/W4312193868","https://openalex.org/W4308165509"],"abstract_inverted_index":{"Recall,":[0],"the":[1,18,49,73,99,134,150,168,173,180,184],"proportion":[2],"of":[3,11,43,48,51,101,133,137,170],"relevant":[4],"documents":[5],"retrieved,":[6],"is":[7,54],"an":[8,46],"important":[9],"measure":[10],"effectiveness":[12],"in":[13,17,76,82],"information":[14],"retrieval,":[15],"particularly":[16],"legal,":[19],"patent,":[20],"and":[21,94,122,128,159,175,178],"medical":[22],"domains.":[23],"Where":[24],"document":[25],"sets":[26],"are":[27,103,108],"too":[28],"large":[29],"for":[30,64,189],"exhaustive":[31],"relevance":[32],"assessment,":[33],"recall":[34,67],"can":[35],"be":[36],"estimated":[37],"by":[38],"assessing":[39],"a":[40,129],"random":[41],"sample":[42],"documents,":[44],"but":[45,107],"indication":[47],"reliability":[50],"this":[52,58,142],"estimate":[53,132],"also":[55],"required.":[56],"In":[57],"article,":[59],"we":[60,115],"examine":[61],"several":[62,154],"methods":[63,96],"estimating":[65],"two-tailed":[66],"confidence":[68],"intervals.":[69],"We":[70,139,161],"find":[71],"that":[72,141],"normal":[74,187],"approximation":[75],"current":[77],"use":[78],"provides":[79],"poor":[80],"coverage":[81,146],"many":[83],"circumstances,":[84],"even":[85],"when":[86],"adjusted":[87],"to":[88,172],"correct":[89],"its":[90],"inappropriate":[91],"symmetry.":[92],"Analytic":[93],"Bayesian":[95],"based":[97],"on":[98,110,120,164],"ratio":[100],"binomials":[102],"generally":[104],"more":[105],"accurate":[106],"inaccurate":[109],"small":[111],"populations.":[112],"The":[113],"method":[114,143],"recommend":[116],"derives":[117],"beta-binomial":[118,182],"posteriors":[119],"retrieved":[121,174],"unretrieved":[123,176],"yield,":[124],"with":[125,183],"fixed":[126],"hyperparameters,":[127],"Monte":[130],"Carlo":[131],"posterior":[135],"distribution":[136],"recall.":[138],"demonstrate":[140],"gives":[144],"mean":[145],"at":[147],"or":[148],"near":[149],"nominal":[151],"level,":[152],"across":[153],"scenarios,":[155],"while":[156],"being":[157],"balanced":[158],"stable.":[160],"offer":[162],"advice":[163],"sampling":[165],"design,":[166],"including":[167],"allocation":[169],"assessments":[171],"segments,":[177],"compare":[179],"proposed":[181],"officially":[185],"reported":[186],"intervals":[188],"recent":[190],"TREC":[191],"Legal":[192],"Track":[193],"iterations.":[194]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}