{"id":"https://openalex.org/W2055601365","doi":"https://doi.org/10.1145/1835449.1835526","title":"Collecting high quality overlapping labels at low cost","display_name":"Collecting high quality overlapping labels at low cost","publication_year":2010,"publication_date":"2010-07-19","ids":{"openalex":"https://openalex.org/W2055601365","doi":"https://doi.org/10.1145/1835449.1835526","mag":"2055601365"},"language":"en","primary_location":{"id":"doi:10.1145/1835449.1835526","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1835449.1835526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","raw_type":"proceedings-article"},"type":"conference-paper","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/A5002485529","display_name":"Grace Hui Yang","orcid":"https://orcid.org/0000-0001-6095-8358"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Yang","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA","Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070188137","display_name":"Anton Mityagin","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anton Mityagin","raw_affiliation_strings":["Microsoft Bing, Redmond, WA, USA","[Microsoft Bing, Redmond, WA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Bing, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"[Microsoft Bing, Redmond, WA, USA]","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019716296","display_name":"Krysta M. Svore","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210156958","display_name":"Marine Ecology and Telemetry Research","ror":"https://ror.org/05jxaw651","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210156958"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krysta M. Svore","raw_affiliation_strings":["Micorsoft Research, Redmond, WA, USA","Micorsoft Research, Redmond, WA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Micorsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I4210156958"]},{"raw_affiliation_string":"Micorsoft Research, Redmond, WA, USA#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023876766","display_name":"S. I. Markov","orcid":"https://orcid.org/0000-0001-8599-2069"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergey Markov","raw_affiliation_strings":["Microsoft Bing, Redmond, WA, USA","[Microsoft Bing, Redmond, WA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Bing, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"[Microsoft Bing, Redmond, WA, USA]","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"459","last_page":"466"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9997000098228455,"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":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9948999881744385,"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/computer-science","display_name":"Computer science","score":0.8135181665420532},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.7127748727798462},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6444458365440369},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6321364641189575},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6107273697853088},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6061098575592041},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5866539478302002},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.534004807472229},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5294280648231506},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5158321261405945},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4576207399368286},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.438278466463089},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3867347240447998},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3643474578857422},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.3048977851867676},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11345463991165161},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08592882752418518}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8135181665420532},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.7127748727798462},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6444458365440369},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6321364641189575},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6107273697853088},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6061098575592041},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5866539478302002},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.534004807472229},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5294280648231506},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5158321261405945},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4576207399368286},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.438278466463089},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3867347240447998},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3643474578857422},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.3048977851867676},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11345463991165161},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08592882752418518},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1835449.1835526","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1835449.1835526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.186.8746","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.186.8746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cmu.edu/%7Ehuiyang/publication/sigir2010.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1970381522","https://openalex.org/W1985554184","https://openalex.org/W2053584122","https://openalex.org/W2083856558","https://openalex.org/W2120724560","https://openalex.org/W2125943921","https://openalex.org/W2128877075","https://openalex.org/W2144660879","https://openalex.org/W2152880776","https://openalex.org/W2166311264","https://openalex.org/W4251560691","https://openalex.org/W6948555412"],"related_works":["https://openalex.org/W2150136235","https://openalex.org/W2053591227","https://openalex.org/W2581240705","https://openalex.org/W3127142483","https://openalex.org/W2041353081","https://openalex.org/W2568183987","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W2971071571"],"abstract_inverted_index":{"This":[0,117],"paper":[1,37,140],"studies":[2],"quality":[3],"of":[4,73,96,111,124,144],"human":[5,30],"labels":[6,56,68,114,148],"used":[7],"to":[8,151],"train":[9],"search":[10,99],"engines'":[11],"rankers.":[12],"Our":[13,86],"specific":[14],"focus":[15],"is":[16,26],"performance":[17],"improvements":[18],"obtained":[19],"by":[20,27,83],"using":[21,125],"overlapping":[22,48,126,147],"relevance":[23],"labels,":[24,50,127,136],"which":[25,43],"collecting":[28],"multiple":[29],"judgments":[31],"for":[32,42,70,77],"each":[33],"training":[34,49,74],"sample.":[35,116],"The":[36,61],"explores":[38],"whether,":[39],"when,":[40],"and":[41],"samples":[44],"one":[45],"should":[46],"obtain":[47],"as":[51,53,129],"well":[52],"how":[54,145],"many":[55,146],"per":[57,115],"sample":[58],"are":[59,80,149],"needed.":[60],"proposed":[62],"selective":[63],"labeling":[64,91,109,118],"scheme":[65,92,119],"collects":[66],"additional":[67],"only":[69],"a":[71,84,107,142],"subset":[72],"samples,":[75],"specifically":[76],"those":[78],"that":[79,89],"labeled":[81],"relevant":[82],"judge.":[85],"experiments":[87],"show":[88],"this":[90],"improves":[93],"the":[94,134,139,153],"NDCG":[95],"two":[97],"Web":[98],"rankers":[100],"on":[101],"several":[102,122],"real-world":[103],"test":[104],"sets,":[105],"with":[106],"low":[108],"overhead":[110],"around":[112],"1.4":[113],"also":[120],"outperforms":[121],"methods":[123],"such":[128],"simple":[130],"k-overlap,":[131],"majority":[132],"vote,":[133],"highest":[135],"etc.":[137],"Finally,":[138],"presents":[141],"study":[143],"needed":[150],"get":[152],"best":[154],"improvement":[155],"in":[156],"retrieval":[157],"accuracy.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
