{"id":"https://openalex.org/W2138957616","doi":"https://doi.org/10.1145/1645953.1646100","title":"Efficient feature weighting methods for ranking","display_name":"Efficient feature weighting methods for ranking","publication_year":2009,"publication_date":"2009-11-02","ids":{"openalex":"https://openalex.org/W2138957616","doi":"https://doi.org/10.1145/1645953.1646100","mag":"2138957616"},"language":"en","primary_location":{"id":"doi:10.1145/1645953.1646100","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1645953.1646100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM 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/A5045521125","display_name":"Hwanjo Yu","orcid":"https://orcid.org/0000-0002-7510-0255"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hwanjo Yu","raw_affiliation_strings":["POSTECH, Pohang, South Korea","Postech, Pohang, South Korea;"],"affiliations":[{"raw_affiliation_string":"POSTECH, Pohang, South Korea","institution_ids":["https://openalex.org/I123900574"]},{"raw_affiliation_string":"Postech, Pohang, South Korea;","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064405745","display_name":"Jinoh Oh","orcid":null},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinoh Oh","raw_affiliation_strings":["POSTECH, Pohang, South Korea","Postech, Pohang, South Korea;"],"affiliations":[{"raw_affiliation_string":"POSTECH, Pohang, South Korea","institution_ids":["https://openalex.org/I123900574"]},{"raw_affiliation_string":"Postech, Pohang, South Korea;","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035744252","display_name":"Wook-Shin Han","orcid":"https://orcid.org/0000-0001-9206-9563"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wook-Shin Han","raw_affiliation_strings":["Kyungbuk National University, Daegu, South Korea"],"affiliations":[{"raw_affiliation_string":"Kyungbuk National University, Daegu, South Korea","institution_ids":["https://openalex.org/I31419693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045521125"],"corresponding_institution_ids":["https://openalex.org/I123900574"],"apc_list":null,"apc_paid":null,"fwci":1.8065,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.88115278,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9943000078201294,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9943000078201294,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9894000291824341,"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/ranking","display_name":"Ranking (information retrieval)","score":0.7947814464569092},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7503153681755066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6911191940307617},{"id":"https://openalex.org/keywords/ranking-svm","display_name":"Ranking SVM","score":0.6757520437240601},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6091164350509644},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.556154727935791},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.514544665813446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5077748894691467},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4748806357383728},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4620688557624817},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4558826684951782},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4556550979614258},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.45144200325012207},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42989373207092285},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4200395941734314},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16743576526641846},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0937032401561737}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7947814464569092},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7503153681755066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6911191940307617},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.6757520437240601},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6091164350509644},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.556154727935791},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.514544665813446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5077748894691467},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4748806357383728},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4620688557624817},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4558826684951782},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4556550979614258},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.45144200325012207},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42989373207092285},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4200395941734314},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16743576526641846},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0937032401561737},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1645953.1646100","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1645953.1646100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM conference on Information and knowledge management","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.613.3780","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.613.3780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://dm.postech.ac.kr/papers/cikm09-rankrelief.pdf","raw_type":"text"},{"id":"pmh:oai:oasis.postech.ac.kr:2014.oak/92225","is_oa":false,"landing_page_url":"https://oasis.postech.ac.kr/handle/2014.oak/92225","pdf_url":null,"source":{"id":"https://openalex.org/S4306401965","display_name":"Open Access System for Information Sharing (Pohang University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I123900574","host_organization_name":"Pohang University of Science and Technology","host_organization_lineage":["https://openalex.org/I123900574"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1500895378","https://openalex.org/W1549887922","https://openalex.org/W1583700199","https://openalex.org/W1808644423","https://openalex.org/W1983575673","https://openalex.org/W2047221353","https://openalex.org/W2071643468","https://openalex.org/W2071664212","https://openalex.org/W2091760137","https://openalex.org/W2101589718","https://openalex.org/W2103235295","https://openalex.org/W2103333826","https://openalex.org/W2109676405","https://openalex.org/W2113762394","https://openalex.org/W2125398996","https://openalex.org/W2133462743","https://openalex.org/W2133956794","https://openalex.org/W2134131174","https://openalex.org/W2142537246","https://openalex.org/W2143331230","https://openalex.org/W2143426320","https://openalex.org/W2435251607","https://openalex.org/W4237617498","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2315491162","https://openalex.org/W2562198007","https://openalex.org/W2368840343","https://openalex.org/W2031468273","https://openalex.org/W2370100764","https://openalex.org/W4297816538","https://openalex.org/W2187479119","https://openalex.org/W2073542340","https://openalex.org/W3127142483","https://openalex.org/W2108728721"],"abstract_inverted_index":{"Feature":[0],"weighting":[1,44,55],"or":[2,21,188],"selection":[3,64,155],"is":[4,101,124,152,182],"a":[5,16,153],"crucial":[6],"process":[7],"to":[8,36,53,206],"identify":[9,207],"an":[10],"important":[11],"subset":[12],"of":[13,29,60,77,85,94,97,148,163,186,200],"features":[14,23,210],"from":[15,175],"data":[17,106,128,202],"set.":[18],"Removing":[19],"irrelevant":[20],"redundant":[22],"can":[24],"improve":[25],"the":[26,61,91,145,161,168,197,208,226,240],"generalization":[27],"performance":[28,109],"ranking":[30,113,136,198],"functions":[31],"in":[32,190,204],"information":[33],"retrieval.":[34],"Due":[35],"fundamental":[37],"differences":[38],"between":[39,82],"classification":[40,48],"and":[41,80,107,121,129,139,171,219,228,235],"ranking,":[42,67,234],"feature":[43,54,63,79,154],"methods":[45],"developed":[46],"for":[47,56,66,104,126,157,178,211,233],"cannot":[49],"be":[50],"readily":[51],"applied":[52],"ranking.":[57,191,212],"A":[58],"state":[59],"art":[62],"method":[65],"called":[68],"GAS,":[69],"has":[70],"been":[71],"recently":[72],"proposed,":[73],"which":[74,123,159],"exploits":[75,160],"importance":[76],"each":[78],"similarity":[81,92],"every":[83],"pair":[84],"features.":[86],"However,":[87,180],"GAS":[88,227,241],"must":[89],"compute":[90],"scores":[93],"all":[95],"pairs":[96],"features,":[98],"thus":[99],"it":[100],"not":[102],"scalable":[103,125],"high-dimensional":[105,127],"its":[108],"degrades":[110],"on":[111,134,144,242],"nonlinear":[112,135],"functions.":[114,137],"This":[115],"paper":[116],"proposes":[117],"novel":[118],"algorithms,":[119],"RankWrapper":[120,138,218],"RankFilter,":[122],"also":[130],"performs":[131],"reasonably":[132],"well":[133],"RankFilter":[140,220],"are":[141],"designed":[142],"based":[143],"key":[146,209],"idea":[147],"Relief":[149,151,230],"algorithm.":[150],"algorithm":[156],"classification,":[158],"notions":[162],"hits":[164,187],"(data":[165,173],"points":[166,174,203],"within":[167],"same":[169],"class)":[170],"misses":[172,189],"different":[176],"classes)":[177],"classification.":[179],"there":[181],"no":[183],"such":[184],"notion":[185],"The":[192],"proposed":[193],"algorithms":[194,231],"instead":[195],"utilize":[196],"distances":[199],"nearest":[201],"order":[205],"Our":[213],"extensive":[214],"experiments":[215],"show":[216],"that":[217],"generate":[221],"higher":[222],"accuracy":[223],"overall":[224],"than":[225,239],"traditional":[229],"adapted":[232],"run":[236],"substantially":[237],"faster":[238],"high":[243],"dimensional":[244],"data.":[245]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":5},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}