{"id":"https://openalex.org/W2964910657","doi":"https://doi.org/10.1609/aaai.v33i01.33014336","title":"Near-Neighbor Methods in Random Preference Completion","display_name":"Near-Neighbor Methods in Random Preference Completion","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2964910657","doi":"https://doi.org/10.1609/aaai.v33i01.33014336","mag":"2964910657"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33014336","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33014336","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4343/4221","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4343/4221","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100346411","display_name":"Ao Liu","orcid":"https://orcid.org/0000-0001-6393-6648"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ao Liu","raw_affiliation_strings":["Rensselaer Polytechnic Institute"],"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014988656","display_name":"Qiong Wu","orcid":"https://orcid.org/0000-0001-7724-8221"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiong Wu","raw_affiliation_strings":["College of William and Mary"],"affiliations":[{"raw_affiliation_string":"College of William and Mary","institution_ids":["https://openalex.org/I16285277"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101738056","display_name":"Zhenming Liu","orcid":"https://orcid.org/0000-0001-9494-8748"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenming Liu","raw_affiliation_strings":["College of William and Mary"],"affiliations":[{"raw_affiliation_string":"College of William and Mary","institution_ids":["https://openalex.org/I16285277"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089639500","display_name":"Lirong Xia","orcid":"https://orcid.org/0000-0002-9800-6691"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lirong Xia","raw_affiliation_strings":["Rensselaer Polytechnic Institute"],"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute","institution_ids":["https://openalex.org/I165799507"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100346411"],"corresponding_institution_ids":["https://openalex.org/I165799507"],"apc_list":null,"apc_paid":null,"fwci":0.931,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80854297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"33","issue":"01","first_page":"4336","last_page":"4343"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9940999746322632,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9940999746322632,"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/T10991","display_name":"Game Theory and Voting Systems","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/complement","display_name":"Complement (music)","score":0.6862308382987976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5987661480903625},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.5894553661346436},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5561283826828003},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5542117357254028},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5202640295028687},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5006301403045654},{"id":"https://openalex.org/keywords/stylized-fact","display_name":"Stylized fact","score":0.46956706047058105},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4678391218185425},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.4668337404727936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45234525203704834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3595505952835083},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33097782731056213},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27968668937683105},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1499905288219452},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09521016478538513}],"concepts":[{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.6862308382987976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5987661480903625},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.5894553661346436},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5561283826828003},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5542117357254028},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5202640295028687},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5006301403045654},{"id":"https://openalex.org/C38935604","wikidata":"https://www.wikidata.org/wiki/Q4330363","display_name":"Stylized fact","level":2,"score":0.46956706047058105},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4678391218185425},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.4668337404727936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45234525203704834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3595505952835083},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33097782731056213},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27968668937683105},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1499905288219452},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09521016478538513},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v33i01.33014336","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33014336","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4343/4221","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33014336","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33014336","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4343/4221","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1752668018","display_name":null,"funder_award_id":"N00014-17-1-2621","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G3256193875","display_name":"CRII: III: Theory and Practice of Learning on Graphs","funder_award_id":"1755769","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4504108201","display_name":null,"funder_award_id":"N00014-17-1","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G4751570384","display_name":null,"funder_award_id":"4-17-1-","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G532064868","display_name":null,"funder_award_id":"1453542","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964910657.pdf","grobid_xml":"https://content.openalex.org/works/W2964910657.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W43928053","https://openalex.org/W126423077","https://openalex.org/W134898465","https://openalex.org/W161037631","https://openalex.org/W184091162","https://openalex.org/W643977996","https://openalex.org/W1526445072","https://openalex.org/W1707761945","https://openalex.org/W1942909375","https://openalex.org/W1948584817","https://openalex.org/W1973435495","https://openalex.org/W2061212083","https://openalex.org/W2062066490","https://openalex.org/W2066459332","https://openalex.org/W2098364948","https://openalex.org/W2110325612","https://openalex.org/W2121808626","https://openalex.org/W2122913573","https://openalex.org/W2125288949","https://openalex.org/W2128678576","https://openalex.org/W2150559086","https://openalex.org/W2157133710","https://openalex.org/W2294759831","https://openalex.org/W2295946735","https://openalex.org/W2400317061","https://openalex.org/W2503048885","https://openalex.org/W2619177611","https://openalex.org/W2788924348","https://openalex.org/W2905524938","https://openalex.org/W2950332743","https://openalex.org/W2950359809","https://openalex.org/W2950514271","https://openalex.org/W2953312250","https://openalex.org/W2963461500","https://openalex.org/W3010805239","https://openalex.org/W4235345084","https://openalex.org/W4295750181","https://openalex.org/W6601741120","https://openalex.org/W6606624662","https://openalex.org/W6631440308","https://openalex.org/W6637631186","https://openalex.org/W6665707008","https://openalex.org/W6667239838","https://openalex.org/W6678360252","https://openalex.org/W6698666064","https://openalex.org/W6738072879","https://openalex.org/W6748961994","https://openalex.org/W7043397492"],"related_works":["https://openalex.org/W1981354176","https://openalex.org/W2351778949","https://openalex.org/W2363993642","https://openalex.org/W2134990190","https://openalex.org/W2978744676","https://openalex.org/W2022364796","https://openalex.org/W2010198938","https://openalex.org/W3116896278","https://openalex.org/W1973215129","https://openalex.org/W2964910657"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"a":[3,16,24,42,112,150],"stylized,":[4],"yet":[5],"natural,":[6],"learning-to-rank":[7],"problem":[8],"and":[9,31,157,166,178],"points":[10],"out":[11],"the":[12,52,56,58,64,66,76,90,98,132,143,159,173],"critical":[13],"incorrectness":[14],"of":[15,37,60,85,119,125,134,145],"widely":[17],"used":[18],"nearest":[19],"neighbor":[20],"algorithm.":[21],"We":[22,148],"consider":[23],"model":[25],"with":[26,41,162],"n":[27],"agents":[28,137],"(users)":[29],"{xi}i\u2208[n]":[30],"m":[32],"alternatives":[33],"(items)":[34],"{yl}l\u2208[m],":[35],"each":[36],"which":[38],"is":[39,80,128,176],"associated":[40],"latent":[43,91,155],"feature":[44,124],"vector.":[45],"Agents":[46],"rank":[47],"items":[48],"nondeterministically":[49],"according":[50],"to":[51,63,81,116,141],"Plackett-Luce":[53],"model,":[54],"where":[55],"higher":[57],"utility":[59],"an":[61,86,120],"item":[62,70],"agent,":[65],"more":[67],"likely":[68],"this":[69],"will":[71],"be":[72],"ranked":[73],"high":[74],"by":[75],"agent.":[77,121],"Our":[78],"goal":[79],"identify":[82],"near":[83],"neighbors":[84,118],"arbitrary":[87],"agent":[88],"in":[89,106],"space":[92],"for":[93,153],"prediction.We":[94],"first":[95],"show":[96],"that":[97,129,172],"Kendall-tau":[99],"distance":[100],"based":[101],"kNN":[102],"produces":[103],"incorrect":[104],"results":[105,161],"our":[107,126],"model.":[108],"Next,":[109],"we":[110],"propose":[111],"new":[113,174],"anchor-based":[114],"algorithm":[115,127,175],"find":[117],"A":[122],"salient":[123],"it":[130],"leverages":[131],"rankings":[133],"many":[135],"other":[136],"(the":[138],"so-called":[139],"\u201canchors\u201d)":[140],"determine":[142],"closeness/similarities":[144],"two":[146],"agents.":[147],"provide":[149],"rigorous":[151],"analysis":[152],"one-dimensional":[154],"space,":[156],"complement":[158],"theoretical":[160],"experiments":[163,170],"on":[164],"synthetic":[165],"real":[167],"datasets.":[168],"The":[169],"confirm":[171],"robust":[177],"practical.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}