{"id":"https://openalex.org/W4290944780","doi":"https://doi.org/10.1145/3534678.3539184","title":"Crowdsourcing with Contextual Uncertainty","display_name":"Crowdsourcing with Contextual Uncertainty","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290944780","doi":"https://doi.org/10.1145/3534678.3539184"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539184","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539184","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5080426723","display_name":"Viet-An Nguyen","orcid":"https://orcid.org/0000-0002-7923-0882"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Viet-An Nguyen","raw_affiliation_strings":["Meta, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007434899","display_name":"Peibei Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peibei Shi","raw_affiliation_strings":["Meta, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101564490","display_name":"Jagdish Ramakrishnan","orcid":"https://orcid.org/0009-0009-3299-4613"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jagdish Ramakrishnan","raw_affiliation_strings":["Meta, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025701093","display_name":"Narjes Torabi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Narjes Torabi","raw_affiliation_strings":["Meta, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102397349","display_name":"Nimar S. Arora","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nimar S. Arora","raw_affiliation_strings":["Meta, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000980244","display_name":"Udi Weinsberg","orcid":"https://orcid.org/0000-0002-6966-1945"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Udi Weinsberg","raw_affiliation_strings":["Meta, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210099336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072100380","display_name":"Michael Tingley","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Tingley","raw_affiliation_strings":["Meta, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210099336"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5080426723"],"corresponding_institution_ids":["https://openalex.org/I4210099336"],"apc_list":null,"apc_paid":null,"fwci":0.9599,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72166538,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"68","issue":null,"first_page":"3645","last_page":"3655"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9970999956130981,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9926000237464905,"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/crowdsourcing","display_name":"Crowdsourcing","score":0.8382455110549927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7930208444595337},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7400668859481812},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6501612663269043},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6055188775062561},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5727216005325317},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.43658921122550964},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12512266635894775}],"concepts":[{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.8382455110549927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7930208444595337},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7400668859481812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6501612663269043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6055188775062561},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5727216005325317},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.43658921122550964},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12512266635894775},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539184","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539184","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1914338220","https://openalex.org/W1972675781","https://openalex.org/W2020018978","https://openalex.org/W2029327121","https://openalex.org/W2063686375","https://openalex.org/W2098865355","https://openalex.org/W2141649520","https://openalex.org/W2147687736","https://openalex.org/W2150612552","https://openalex.org/W2254249950","https://openalex.org/W2295951612","https://openalex.org/W2548695521","https://openalex.org/W2577537660","https://openalex.org/W2585226541","https://openalex.org/W2764320286","https://openalex.org/W2769041395","https://openalex.org/W2901679674","https://openalex.org/W2947390390","https://openalex.org/W2959716049","https://openalex.org/W2963995504","https://openalex.org/W3080755960","https://openalex.org/W3101522374","https://openalex.org/W3114228236","https://openalex.org/W4293409613"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W1503094549","https://openalex.org/W4384486036","https://openalex.org/W135177976","https://openalex.org/W2337920774","https://openalex.org/W4318823662","https://openalex.org/W2886410948","https://openalex.org/W2025875869","https://openalex.org/W3207526114","https://openalex.org/W4286908577"],"abstract_inverted_index":{"We":[0,29,94],"study":[1],"a":[2,14,26,32,120],"crowdsourcing":[3],"setting":[4],"where":[5],"we":[6,80],"need":[7],"to":[8,65,110],"infer":[9],"the":[10,23,45,51,58,67,72],"latent":[11],"truth":[12],"about":[13],"task":[15],"given":[16],"observed":[17],"labels":[18,108],"together":[19],"with":[20],"context":[21],"in":[22,102],"form":[24],"of":[25,47,53,57,69,74],"classifier":[27,59,75],"score.":[28,60],"present":[30],"Theodon,":[31],"hierarchical":[33],"non-parametric":[34],"Bayesian":[35],"model,":[36],"developed":[37],"and":[38,50,123],"deployed":[39],"at":[40,87],"Meta,":[41],"that":[42,96],"captures":[43],"both":[44],"prevalence":[46],"label":[48],"categories":[49],"accuracy":[52],"labelers":[54],"as":[55,89,91,119],"functions":[56],"Theodon":[61,97],"uses":[62],"Gaussian":[63],"processes":[64],"model":[66],"non-uniformity":[68],"mistakes":[70],"over":[71],"range":[73],"scores.":[76],"For":[77],"our":[78],"experiments,":[79],"used":[81],"data":[82],"generated":[83],"from":[84],"integrity":[85],"applications":[86],"Meta":[88],"well":[90],"public":[92,114],"datasets.":[93],"showed":[95],"(1)":[98],"obtains":[99],"1-4%":[100],"improvement":[101],"AUC-PR":[103],"predictions":[104],"on":[105,128],"items'":[106],"true":[107],"compared":[109],"state-of-the-art":[111],"baselines":[112],"for":[113],"datasets,":[115],"(2)":[116],"is":[117],"effective":[118],"calibration":[121],"method,":[122],"(3)":[124],"provides":[125],"detailed":[126],"insights":[127],"labelers'":[129],"performances.":[130]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}
