{"id":"https://openalex.org/W2096937925","doi":"https://doi.org/10.1145/1148170.1148246","title":"High accuracy retrieval with multiple nested ranker","display_name":"High accuracy retrieval with multiple nested ranker","publication_year":2006,"publication_date":"2006-08-06","ids":{"openalex":"https://openalex.org/W2096937925","doi":"https://doi.org/10.1145/1148170.1148246","mag":"2096937925"},"language":"en","primary_location":{"id":"doi:10.1145/1148170.1148246","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1148170.1148246","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th annual 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/A5002387873","display_name":"Irina Matveeva","orcid":"https://orcid.org/0000-0002-8406-6116"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Irina Matveeva","raw_affiliation_strings":["University of Chicago, Chicago, IL"],"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, IL","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069708056","display_name":"Chris 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":"Chris Burges","raw_affiliation_strings":["Microsoft Research, Redmond, WA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075358514","display_name":"Timo Burkard","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133358","display_name":"Search","ror":"https://ror.org/03f78hn46","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210133358"]},{"id":"https://openalex.org/I4210126048","display_name":"MSNW (United States)","ror":"https://ror.org/03558b563","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126048"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timo Burkard","raw_affiliation_strings":["MSN Search, Redmond, WA"],"affiliations":[{"raw_affiliation_string":"MSN Search, Redmond, WA","institution_ids":["https://openalex.org/I4210126048","https://openalex.org/I4210133358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004360932","display_name":"Andy Laucius","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":"Andy Laucius","raw_affiliation_strings":["Microsoft Research, Redmond, WA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101604711","display_name":"Leon Wong","orcid":"https://orcid.org/0000-0001-9937-1714"},"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":"Leon Wong","raw_affiliation_strings":["Microsoft Research, Redmond, WA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5002387873"],"corresponding_institution_ids":["https://openalex.org/I40347166"],"apc_list":null,"apc_paid":null,"fwci":21.5466,"has_fulltext":false,"cited_by_count":132,"citation_normalized_percentile":{"value":0.99184925,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"437","last_page":"444"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9987000226974487,"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":0.9987000226974487,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9962999820709229,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9962999820709229,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.8631033301353455},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7965946197509766},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7793008089065552},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.7061539888381958},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6152133941650391},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5600623488426208},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5450856685638428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4439057409763336},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4343263506889343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4313584566116333},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4065471887588501},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15846672654151917}],"concepts":[{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.8631033301353455},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7965946197509766},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7793008089065552},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7061539888381958},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6152133941650391},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5600623488426208},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5450856685638428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4439057409763336},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4343263506889343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4313584566116333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4065471887588501},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15846672654151917},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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":2,"locations":[{"id":"doi:10.1145/1148170.1148246","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1148170.1148246","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.89.4343","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.89.4343","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/~cburges/papers/telescoping_final.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"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":28,"referenced_works":["https://openalex.org/W69517937","https://openalex.org/W286550156","https://openalex.org/W1501307387","https://openalex.org/W1510014385","https://openalex.org/W1557757161","https://openalex.org/W1903402718","https://openalex.org/W1985554184","https://openalex.org/W2053584122","https://openalex.org/W2066867064","https://openalex.org/W2070534370","https://openalex.org/W2073853190","https://openalex.org/W2115843962","https://openalex.org/W2116442280","https://openalex.org/W2143331230","https://openalex.org/W2149397822","https://openalex.org/W2151058089","https://openalex.org/W2152314154","https://openalex.org/W2154872931","https://openalex.org/W2164547069","https://openalex.org/W2914484425","https://openalex.org/W4238404964","https://openalex.org/W4251560691","https://openalex.org/W4285719527","https://openalex.org/W4298421000","https://openalex.org/W6610337231","https://openalex.org/W6677510188","https://openalex.org/W6681983783","https://openalex.org/W6682644385"],"related_works":["https://openalex.org/W4385565564","https://openalex.org/W2293317945","https://openalex.org/W2122040421","https://openalex.org/W2041353081","https://openalex.org/W104148947","https://openalex.org/W4323349240","https://openalex.org/W2118669775","https://openalex.org/W54129904","https://openalex.org/W3199233695","https://openalex.org/W2470818894"],"abstract_inverted_index":{"High":[0],"precision":[1,144],"at":[2,28,145],"the":[3,19,26,29,35,45,54,58,71,77,98,106,114,119,123,126,134,139,146,153],"top":[4,30,36,140,147],"ranks":[5,31],"has":[6],"become":[7],"a":[8,51,67,87],"new":[9,68],"focus":[10],"of":[11,53,70,94,122,152],"research":[12],"in":[13,125,150],"information":[14],"retrieval.":[15],"This":[16,56],"paper":[17],"presents":[18],"multiple":[20],"nested":[21],"ranker":[22],"approach":[23,43,82],"that":[24,132],"improves":[25,143],"accuracy":[27],"by":[32,76],"iteratively":[33],"re-ranking":[34],"scoring":[37,141],"documents.":[38],"At":[39],"each":[40],"iteration,":[41],"this":[42,81],"uses":[44],"RankNet":[46],"learning":[47,135],"algorithm":[48,136],"to":[49,73,104],"re-rank":[50],"subset":[52],"results.":[55],"splits":[57],"problem":[59],"into":[60],"smaller":[61],"and":[62,65],"easier":[63],"tasks":[64],"generates":[66],"distribution":[69],"results":[72,142],"be":[74],"learned":[75],"algorithm.":[78],"We":[79,96],"evaluate":[80],"using":[83],"different":[84],"settings":[85],"on":[86,113,118,138],"data":[88],"set":[89],"labeled":[90],"with":[91],"several":[92],"degrees":[93],"relevance.":[95],"use":[97],"normalized":[99],"discounted":[100],"cumulative":[101],"gain":[102],"(NDCG)":[103],"measure":[105],"performance":[107],"because":[108],"it":[109],"depends":[110],"not":[111],"only":[112],"position":[115],"but":[116],"also":[117],"relevance":[120],"score":[121],"document":[124],"ranked":[127],"list.":[128],"Our":[129],"experiments":[130],"show":[131],"making":[133],"concentrate":[137],"ten":[148],"documents":[149],"terms":[151],"NDCG":[154],"score.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":5}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}