{"id":"https://openalex.org/W2894874337","doi":"https://doi.org/10.1145/3209280.3232788","title":"The Quest for Total Recall","display_name":"The Quest for Total Recall","publication_year":2018,"publication_date":"2018-08-28","ids":{"openalex":"https://openalex.org/W2894874337","doi":"https://doi.org/10.1145/3209280.3232788","mag":"2894874337"},"language":"en","primary_location":{"id":"doi:10.1145/3209280.3232788","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3209280.3232788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Symposium on Document Engineering 2018","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/A5084091807","display_name":"Gordon V. Cormack","orcid":"https://orcid.org/0000-0002-5890-0293"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Gordon V. Cormack","raw_affiliation_strings":["University of Waterloo"],"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083981495","display_name":"Maura R. Grossman","orcid":"https://orcid.org/0000-0003-2279-4262"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Maura R. Grossman","raw_affiliation_strings":["University of Waterloo"],"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084091807"],"corresponding_institution_ids":["https://openalex.org/I151746483"],"apc_list":null,"apc_paid":null,"fwci":0.2117,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60585996,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9943000078201294,"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"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9943000078201294,"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/T10028","display_name":"Topic Modeling","score":0.9843000173568726,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9785000085830688,"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/due-diligence","display_name":"Due diligence","score":0.6375990509986877},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.6277279257774353},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5718247294425964},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5628010034561157},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4667375981807709},{"id":"https://openalex.org/keywords/haystack","display_name":"Haystack","score":0.44627413153648376},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42036721110343933},{"id":"https://openalex.org/keywords/government","display_name":"Government (linguistics)","score":0.42003124952316284},{"id":"https://openalex.org/keywords/enforcement","display_name":"Enforcement","score":0.41753190755844116},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.39095306396484375},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.3827378749847412},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.27966558933258057},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.22950300574302673},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.1954016089439392},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.16161152720451355},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.12863853573799133},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12695544958114624}],"concepts":[{"id":"https://openalex.org/C2781016034","wikidata":"https://www.wikidata.org/wiki/Q794134","display_name":"Due diligence","level":2,"score":0.6375990509986877},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.6277279257774353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5718247294425964},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5628010034561157},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4667375981807709},{"id":"https://openalex.org/C13424479","wikidata":"https://www.wikidata.org/wiki/Q5687237","display_name":"Haystack","level":2,"score":0.44627413153648376},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42036721110343933},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.42003124952316284},{"id":"https://openalex.org/C2779777834","wikidata":"https://www.wikidata.org/wiki/Q4202277","display_name":"Enforcement","level":2,"score":0.41753190755844116},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.39095306396484375},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3827378749847412},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.27966558933258057},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.22950300574302673},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.1954016089439392},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.16161152720451355},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.12863853573799133},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12695544958114624},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3209280.3232788","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3209280.3232788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Symposium on Document Engineering 2018","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W179309874","https://openalex.org/W1700671489","https://openalex.org/W2029075138","https://openalex.org/W2122053905","https://openalex.org/W2341384651","https://openalex.org/W2533861448","https://openalex.org/W2565695915","https://openalex.org/W2741811485","https://openalex.org/W2742025582","https://openalex.org/W2751819974","https://openalex.org/W2798698938"],"related_works":["https://openalex.org/W4253878822","https://openalex.org/W1965563707","https://openalex.org/W4210692028","https://openalex.org/W1736550718","https://openalex.org/W2808729870","https://openalex.org/W2479343091","https://openalex.org/W2278064783","https://openalex.org/W3174858427","https://openalex.org/W2358294942","https://openalex.org/W4367460280"],"abstract_inverted_index":{"The":[0],"objective":[1,144,162,195],"of":[2,21,94],"high-recall":[3],"information":[4,12,16,140,169,182],"retrieval":[5,141,183],"(HRIR)":[6],"is":[7,145,163,177],"to":[8,14,52,59,146,164,188],"identify":[9,147],"substantially":[10],"all":[11,152,191],"relevant":[13,153,166,192],"an":[15,194],"need,":[17],"where":[18,142,160],"the":[19,60,69,92,143,148,161,186],"consequences":[20],"missing":[22],"or":[23,35,65,158],"untimely":[24],"results":[25],"may":[26],"have":[27],"serious":[28],"legal,":[29,61],"policy,":[30],"health,":[31],"social,":[32],"safety,":[33],"defence,":[34],"financial":[36],"implications.":[37],"To":[38],"find":[39],"acceptance":[40],"in":[41,82,91,101,112,118],"practice,":[42,57],"HRIR":[43,135,176],"technologies":[44],"must":[45,49],"be":[46,50,53],"more":[47,54],"effective---and":[48],"shown":[51],"effective---than":[55],"current":[56],"according":[58],"statutory,":[62],"regulatory,":[63],"ethical,":[64],"professional":[66],"standards":[67],"governing":[68],"application":[70],"domain.":[71],"Such":[72],"domains":[73],"include,":[74],"but":[75],"are":[76,208],"not":[77,209],"limited":[78],"to,":[79],"electronic":[80],"discovery":[81],"legal":[83],"proceedings;":[84],"distinguishing":[85],"between":[86],"public":[87],"and":[88,106,124,127,129,155,201,206],"non-public":[89],"records":[90],"curation":[93],"government":[95],"archives;":[96],"systematic":[97],"review":[98],"for":[99,196],"meta-analysis":[100],"evidence-based":[102],"medicine;":[103],"separating":[104],"irregularities":[105],"intentional":[107],"misstatements":[108],"from":[109,137,156,167,180],"unintentional":[110],"errors":[111],"accounting":[113],"restatements;":[114],"performing":[115],"\"due":[116],"diligence\"":[117],"connection":[119],"with":[120],"pending":[121],"mergers,":[122],"acquisitions,":[123],"financing":[125],"transactions;":[126],"surveillance":[128],"compliance":[130],"activities":[131],"involving":[132],"massive":[133],"datasets.":[134],"differs":[136],"ad":[138],"hoc":[139],"best,":[149],"rather":[150],"than":[151],"information,":[154],"classification":[157],"categorization":[159],"separate":[165],"non-relevant":[168],"based":[170],"on":[171],"previously":[172],"labeled":[173],"training":[174],"examples.":[175],"further":[178],"differentiated":[179],"established":[181],"applications":[184],"by":[185],"need":[187],"quantify":[189],"\"substantially":[190],"information\";":[193],"which":[197],"existing":[198],"evaluation":[199],"strategies":[200],"measures,":[202],"such":[203],"as":[204],"precision":[205],"recall,":[207],"particularly":[210],"well":[211],"suited.":[212]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}