{"id":"https://openalex.org/W2145664829","doi":"https://doi.org/10.1145/1963405.1963459","title":"Learning to rank with multiple objective functions","display_name":"Learning to rank with multiple objective functions","publication_year":2011,"publication_date":"2011-03-28","ids":{"openalex":"https://openalex.org/W2145664829","doi":"https://doi.org/10.1145/1963405.1963459","mag":"2145664829"},"language":"en","primary_location":{"id":"doi:10.1145/1963405.1963459","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1963405.1963459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th international conference on World wide web","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/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"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Krysta M. Svore","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027341076","display_name":"Maksims Volkovs","orcid":"https://orcid.org/0009-0007-0561-2187"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Maksims N. Volkovs","raw_affiliation_strings":["University of Toronto, Toronto, ON, Canada","University of Toronto, Toronto, On, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]},{"raw_affiliation_string":"University of Toronto, Toronto, On, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034285513","display_name":"Christopher J. C. Burges","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":"Christopher J.C. Burges","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":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019716296"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":12.9955,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.98405154,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"367","last_page":"376"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.992900013923645,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9891999959945679,"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":0.8472193479537964},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.7904679179191589},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7634994387626648},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7381548881530762},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.7176782488822937},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.614558219909668},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5065227746963501},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4830223023891449},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4700321853160858},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.430422306060791},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3265075385570526},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.26180577278137207},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2230248749256134}],"concepts":[{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.8472193479537964},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.7904679179191589},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7634994387626648},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7381548881530762},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7176782488822937},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.614558219909668},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5065227746963501},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4830223023891449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4700321853160858},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.430422306060791},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3265075385570526},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26180577278137207},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2230248749256134},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1963405.1963459","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1963405.1963459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th international conference on World wide web","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.205.8837","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.8837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.www2011india.com/proceeding/proceedings/p367.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.207.5582","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.207.5582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/en-us/um/people/cburges/papers/multiobjective.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1564163720","https://openalex.org/W1678356000","https://openalex.org/W1974360117","https://openalex.org/W1985554184","https://openalex.org/W2047221353","https://openalex.org/W2059001985","https://openalex.org/W2106630408","https://openalex.org/W2108862644","https://openalex.org/W2113640060","https://openalex.org/W2115584760","https://openalex.org/W2125771191","https://openalex.org/W2128877075","https://openalex.org/W2135645798","https://openalex.org/W2140634465","https://openalex.org/W2143160289","https://openalex.org/W2143331230","https://openalex.org/W2159545104","https://openalex.org/W2162059449","https://openalex.org/W2883070021","https://openalex.org/W4251560691","https://openalex.org/W6607690188"],"related_works":["https://openalex.org/W2150136235","https://openalex.org/W2053591227","https://openalex.org/W2041353081","https://openalex.org/W2581240705","https://openalex.org/W3127142483","https://openalex.org/W2568183987","https://openalex.org/W3160516639","https://openalex.org/W4385565564","https://openalex.org/W2138488530","https://openalex.org/W2898073868"],"abstract_inverted_index":{"We":[0,20,162,213],"investigate":[1,214],"the":[2,12,51,79,93,96,106,115,125,135,155,209],"problem":[3,52,117],"of":[4,14,53,58,137,167],"learning":[5,15,28,54],"to":[6,23,29,101,151,171],"rank":[7,136],"with":[8,190,208],"document":[9],"retrieval":[10],"from":[11,55,87],"perspective":[13],"for":[16,78,92,129,159,187,196],"multiple":[17,35],"objective":[18],"functions.":[19],"present":[21],"solutions":[22],"two":[24],"open":[25],"problems":[26,169],"in":[27,132,202,206],"rank:":[30],"first,":[31],"we":[32,66,112],"show":[33,67,163],"how":[34,164],"measures":[36,59],"can":[37,46,118,140],"be":[38,47,120,141],"combined":[39],"into":[40],"a":[41,56,70,83,180,203,219],"single":[42],"graded":[43],"measure":[44,74,85,98,108],"that":[45,114,177,183,192],"learned.":[48],"This":[49],"solves":[50],"'scorecard'":[57],"by":[60],"making":[61],"such":[62],"scorecards":[63],"comparable,":[64],"and":[65,82],"results":[68,201],"where":[69],"standard":[71],"web":[72],"relevance":[73,84],"(NDCG)":[75],"is":[76,90,99,184,193],"used":[77,91],"top-tier":[80,107],"measure,":[81],"derived":[86],"click":[88],"data":[89],"second-tier":[94,97],"measure;":[95],"shown":[100],"significantly":[102],"improve":[103],"while":[104],"leaving":[105],"largely":[109],"unchanged.":[110],"Second,":[111],"note":[113],"learning-to-rank":[116],"itself":[119],"viewed":[121],"as":[122,124],"changing":[123],"ranking":[126,221],"model":[127],"learns:":[128],"example,":[130],"early":[131,188],"learning,":[133,189],"adjusting":[134],"all":[138],"documents":[139,158],"advantageous,":[142],"but":[143],"later":[144],"during":[145],"training,":[146],"it":[147],"becomes":[148],"more":[149,185,194],"desirable":[150],"concentrate":[152],"on":[153],"correcting":[154],"top":[156],"few":[157],"each":[160],"query.":[161],"an":[165,172],"analysis":[166],"these":[168,215],"leads":[170],"improved,":[173],"iteration-dependent":[174],"cost":[175,181],"function":[176,182],"interpolates":[178],"between":[179],"appropriate":[186,195],"one":[191],"late-stage":[197],"learning.":[198],"The":[199],"approach":[200],"significant":[204],"improvement":[205],"accuracy":[207],"same":[210],"size":[211],"models.":[212],"ideas":[216],"using":[217],"LambdaMART,":[218],"state-of-the-art":[220],"algorithm.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":8}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}