{"id":"https://openalex.org/W2009592498","doi":"https://doi.org/10.1145/2806416.2806492","title":"Aggregation of Crowdsourced Ordinal Assessments and Integration with Learning to Rank","display_name":"Aggregation of Crowdsourced Ordinal Assessments and Integration with Learning to Rank","publication_year":2015,"publication_date":"2015-10-17","ids":{"openalex":"https://openalex.org/W2009592498","doi":"https://doi.org/10.1145/2806416.2806492","mag":"2009592498"},"language":"en","primary_location":{"id":"doi:10.1145/2806416.2806492","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2806416.2806492","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","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/A5028029900","display_name":"Pavel Metrikov","orcid":null},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pavel Metrikov","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056048295","display_name":"Virgil Pavlu","orcid":null},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Virgil Pavlu","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107005206","display_name":"Javed A. Aslam","orcid":"https://orcid.org/0009-0006-5098-6594"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Javed A. Aslam","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028029900"],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":2.5141,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.90920583,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1391","last_page":"1400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9998999834060669,"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":0.9998999834060669,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9919999837875366,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9907000064849854,"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/relevance","display_name":"Relevance (law)","score":0.8810628652572632},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7903581261634827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7655047178268433},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5910346508026123},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.5673317909240723},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5634506940841675},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5393111705780029},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5002245903015137},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4733572006225586},{"id":"https://openalex.org/keywords/ordinal-data","display_name":"Ordinal data","score":0.44801706075668335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.384633332490921},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36226850748062134},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34628283977508545},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.22190922498703003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14083504676818848},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.13014522194862366}],"concepts":[{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.8810628652572632},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7903581261634827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7655047178268433},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5910346508026123},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.5673317909240723},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5634506940841675},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5393111705780029},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5002245903015137},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4733572006225586},{"id":"https://openalex.org/C85461838","wikidata":"https://www.wikidata.org/wiki/Q7100785","display_name":"Ordinal data","level":2,"score":0.44801706075668335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.384633332490921},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36226850748062134},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34628283977508545},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.22190922498703003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14083504676818848},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.13014522194862366},{"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2806416.2806492","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2806416.2806492","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3949784347","display_name":null,"funder_award_id":"1421399","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W9014458","https://openalex.org/W69540849","https://openalex.org/W1506806321","https://openalex.org/W1678356000","https://openalex.org/W1738124305","https://openalex.org/W1902046146","https://openalex.org/W1938221098","https://openalex.org/W1966576448","https://openalex.org/W1989621150","https://openalex.org/W1990190154","https://openalex.org/W2006226534","https://openalex.org/W2011039951","https://openalex.org/W2051039162","https://openalex.org/W2054953618","https://openalex.org/W2072147212","https://openalex.org/W2094145178","https://openalex.org/W2103850933","https://openalex.org/W2111787673","https://openalex.org/W2115584760","https://openalex.org/W2125943921","https://openalex.org/W2128475742","https://openalex.org/W2129345386","https://openalex.org/W2131864341","https://openalex.org/W2134305421","https://openalex.org/W2141649520","https://openalex.org/W2142518823","https://openalex.org/W2152009989","https://openalex.org/W2164545125","https://openalex.org/W2784672094","https://openalex.org/W2884475480","https://openalex.org/W2952595241","https://openalex.org/W6611090737","https://openalex.org/W6677385034","https://openalex.org/W6679158198","https://openalex.org/W6682675497","https://openalex.org/W6747597888"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W135177976","https://openalex.org/W4384486036","https://openalex.org/W1503094549","https://openalex.org/W2337920774","https://openalex.org/W2772359885","https://openalex.org/W3011471740","https://openalex.org/W2884580467","https://openalex.org/W2544639518","https://openalex.org/W2572315477"],"abstract_inverted_index":{"Existing":[0],"approaches":[1,50],"used":[2],"for":[3,27,37,104],"training":[4],"and":[5,51,62,82,107],"evaluating":[6],"search":[7],"engines":[8],"often":[9],"rely":[10],"on":[11],"crowdsourced":[12,45,92],"assessments":[13,26],"of":[14,40,67,72,97],"document":[15,42],"relevance":[16,43,73,81,98],"with":[17],"respect":[18],"to":[19],"a":[20,34],"user":[21],"query.":[22],"To":[23],"use":[24],"such":[25],"either":[28],"evaluation":[29],"or":[30],"learning,":[31],"we":[32,58,78],"propose":[33],"new":[35],"framework":[36],"the":[38,65],"inference":[39,96],"true":[41,80],"from":[44,91],"data---one":[46],"simpler":[47],"than":[48],"previous":[49],"achieving":[52],"better":[53,95],"performance.":[54],"For":[55,75],"each":[56,76],"assessor,":[57],"model":[59,79],"assessor":[60],"quality":[61],"bias":[63],"in":[64],"form":[66],"Gaussian":[68],"distributed":[69],"class":[70],"conditionals":[71],"grades.":[74],"document,":[77],"difficulty":[83],"as":[84,99,101],"continuous":[85],"variables.":[86],"We":[87],"estimate":[88],"all":[89],"parameters":[90],"data,":[93],"demonstrating":[94],"well":[100],"realistic":[102],"models":[103],"both":[105],"documents":[106],"assessors.":[108]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
