{"id":"https://openalex.org/W2037080275","doi":"https://doi.org/10.1145/2348283.2348455","title":"Active query selection for learning rankers","display_name":"Active query selection for learning rankers","publication_year":2012,"publication_date":"2012-08-12","ids":{"openalex":"https://openalex.org/W2037080275","doi":"https://doi.org/10.1145/2348283.2348455","mag":"2037080275"},"language":"en","primary_location":{"id":"doi:10.1145/2348283.2348455","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2348283.2348455","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval","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/A5038378351","display_name":"Mustafa Bilgic","orcid":"https://orcid.org/0000-0001-5123-9992"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mustafa Bilgic","raw_affiliation_strings":["Illinois Institute of Technology, Chicago, IL, USA","[Illinois Institute of Technology, Chicago, IL, USA.]"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology, Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]},{"raw_affiliation_string":"[Illinois Institute of Technology, Chicago, IL, USA.]","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102869952","display_name":"Paul N. Bennett","orcid":"https://orcid.org/0000-0002-8846-5480"},"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":"Paul N. Bennett","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038378351"],"corresponding_institution_ids":["https://openalex.org/I180949307"],"apc_list":null,"apc_paid":null,"fwci":0.8918,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.79538113,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1033","last_page":"1034"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9969000220298767,"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":0.9934999942779541,"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/learning-to-rank","display_name":"Learning to rank","score":0.789854109287262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7851510047912598},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6334115862846375},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6271467208862305},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5756737589836121},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5728824138641357},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5415608286857605},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.4596211016178131},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4102585017681122},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36392742395401},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.32000023126602173},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1461809277534485},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12412193417549133},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.10182100534439087}],"concepts":[{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.789854109287262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7851510047912598},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6334115862846375},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6271467208862305},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5756737589836121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5728824138641357},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5415608286857605},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.4596211016178131},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4102585017681122},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36392742395401},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.32000023126602173},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1461809277534485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12412193417549133},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.10182100534439087},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2348283.2348455","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2348283.2348455","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval","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":5,"referenced_works":["https://openalex.org/W1857290810","https://openalex.org/W2031972533","https://openalex.org/W2093347820","https://openalex.org/W2124504084","https://openalex.org/W2130492741"],"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/W4390446658"],"abstract_inverted_index":{"Methods":[0],"that":[1,52,74],"reduce":[2],"the":[3,87],"amount":[4],"of":[5],"labeled":[6],"data":[7],"needed":[8],"for":[9],"training":[10],"have":[11],"focused":[12],"more":[13,81],"on":[14,21],"selecting":[15],"which":[16,22,42],"documents":[17],"to":[18,29,40,50,63,67],"label":[19],"than":[20,83],"queries":[23,43],"should":[24,44],"be":[25,45],"labeled.":[26],"One":[27],"exception":[28],"this":[30,58],"(Long":[31],"et":[32],"al.":[33],"2010)":[34],"uses":[35],"expected":[36,76],"loss":[37,77],"optimization":[38],"(ELO)":[39],"estimate":[41],"selected":[46],"but":[47],"is":[48,80,91],"limited":[49],"rankers":[51],"predict":[53],"absolute":[54],"graded":[55],"relevance.":[56],"In":[57],"work,":[59],"we":[60],"demonstrate":[61],"how":[62],"easily":[64],"adapt":[65],"ELO":[66],"work":[68],"with":[69],"any":[70],"ranker":[71],"and":[72],"show":[73],"estimating":[75],"in":[78],"DCG":[79],"robust":[82],"NDCG":[84],"even":[85],"when":[86],"final":[88],"performance":[89],"measure":[90],"NDCG.":[92]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}