{"id":"https://openalex.org/W7160958161","doi":"https://doi.org/10.48550/arxiv.2605.09653","title":"A Scalable and Unified Framework to Weighted Rank Aggregation","display_name":"A Scalable and Unified Framework to Weighted Rank Aggregation","publication_year":2026,"publication_date":"2026-05-10","ids":{"openalex":"https://openalex.org/W7160958161","doi":"https://doi.org/10.48550/arxiv.2605.09653"},"language":"en","primary_location":{"id":"pmh:doi:10.4230/lipics.icalp.2026.49","is_oa":true,"landing_page_url":"https://aclanthology.org/L12-1624/","pdf_url":"http://www.vldb.org/pvldb/vol13/p2706-kuhlman.pdf","source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},"type":"conference-paper","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://www.vldb.org/pvldb/vol13/p2706-kuhlman.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074358236","display_name":"Amir Carmel","orcid":"https://orcid.org/0000-0002-0784-886X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carmel, Amir","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135955543","display_name":"Debarati Das","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Das, Debarati","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135952320","display_name":"Tien-Long Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Tien-Long","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.60229689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10991","display_name":"Game Theory and Voting Systems","score":0.957099974155426,"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"}},"topics":[{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.957099974155426,"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.010999999940395355,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.005799999926239252,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.6722999811172485},{"id":"https://openalex.org/keywords/hamming-distance","display_name":"Hamming distance","score":0.6241999864578247},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.5932000279426575},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5468999743461609},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5080000162124634},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5005999803543091},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49300000071525574}],"concepts":[{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.6722999811172485},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.6241999864578247},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.5932000279426575},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5526000261306763},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5468999743461609},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5080000162124634},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5005999803543091},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49300000071525574},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4569999873638153},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.4343999922275543},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41290000081062317},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.39820000529289246},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38269999623298645},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35839998722076416},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.34279999136924744},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.33230000734329224},{"id":"https://openalex.org/C73150493","wikidata":"https://www.wikidata.org/wiki/Q853922","display_name":"Hamming code","level":4,"score":0.2912999987602234},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.266400009393692},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.4230/lipics.icalp.2026.49","is_oa":true,"landing_page_url":"https://aclanthology.org/L12-1624/","pdf_url":"http://www.vldb.org/pvldb/vol13/p2706-kuhlman.pdf","source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},{"id":"doi:10.48550/arxiv.2605.09653","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09653","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.4230/lipics.icalp.2026.49","is_oa":true,"landing_page_url":"https://aclanthology.org/L12-1624/","pdf_url":"http://www.vldb.org/pvldb/vol13/p2706-kuhlman.pdf","source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6218183636665344}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7160958161.pdf","grobid_xml":"https://content.openalex.org/works/W7160958161.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"rank":[1,8,72,144,156],"aggregation":[2,73,157],"problem":[3],"seeks":[4],"to":[5,55,66,109,126,180,232,277],"combine":[6],"multiple":[7],"orderings":[9],"of":[10,14,47,63,115,187,216,239,266],"the":[11,41,52,61,118,127,159,165,181,213,233,257,264,278],"same":[12],"set":[13,46],"candidates":[15],"into":[16],"a":[17,45,57,97,103,112,123,138,151,174,177,184,226,229,236],"single":[18],"consensus":[19],"ordering.":[20],"Such":[21],"problems":[22],"arise":[23],"in":[24,164,183,193,199,235,245,253],"diverse":[25],"domains,":[26],"including":[27],"web":[28],"search,":[29],"employment,":[30],"college":[31],"admissions,":[32],"and":[33,85,195,211,218,247,262],"voting.":[34],"In":[35],"this":[36],"work":[37],"we":[38,149,224,260],"focus":[39,110],"on":[40,111,147],"1-median":[42,182,234],"objective:":[43],"given":[44],"m":[48],"rankings":[49],"over":[50],"[n],":[51],"goal":[53],"is":[54],"compute":[56],"ranking":[58],"that":[59,101,162,274],"minimizes":[60],"sum":[62],"its":[64],"distances":[65],"all":[67],"input":[68],"rankings.":[69],"We":[70,201],"study":[71],"under":[74,158],"several":[75],"classical":[76],"distance":[77,135,161],"metrics:":[78],"Ulam":[79,160,258],"distance,":[80,84,259],"Spearman's":[81,209],"footrule,":[82],"Hamming":[83,217],"Kendall-tau,":[86],"as":[87,89],"well":[88],"their":[90],"weighted":[91,143,279],"variants.":[92],"Our":[93,171],"contributions":[94],"begin":[95],"with":[96],"novel":[98],"unified":[99],"framework":[100,141],"identifies":[102],"key":[104],"structural":[105],"property:":[106],"it":[107],"suffices":[108],"small":[113],"subset":[114],"rankings,":[116],"where":[117],"corresponding":[119],"local":[120,190,242],"one-median":[121],"provides":[122],"good":[124],"approximation":[125,153,206],"global":[128],"median.":[129],"This":[130],"principle":[131],"extends":[132,276],"across":[133],"these":[134],"measures,":[136],"yielding":[137],"general":[139],"algorithmic":[140],"for":[142,155,176,208,212,228,256],"aggregation.":[145],"Building":[146],"this,":[148],"present":[150],"new":[152,204],"algorithm":[154,172],"scales":[163],"Massively":[166],"Parallel":[167],"Computation":[168],"(MPC)":[169],"model.":[170],"computes":[173],"$(2-\u03b1)$-approximation,":[175],"constant":[178,185,230,237],"$\u03b1&gt;0$,":[179],"number":[186,238],"rounds,":[188,240],"using":[189,241],"memory":[191,197,243,249],"sublinear":[192,244],"n":[194,246],"total":[196,248],"near-linear":[198,252],"n.":[200,254],"further":[202,275],"design":[203],"MPC":[205],"algorithms":[207],"footrule":[210],"element-weighted":[214],"variants":[215],"Kendall-tau":[219],"distances.":[220],"For":[221],"each":[222],"metric,":[223],"obtain":[225],"$(2-\u03b6)$-approximation,":[227],"$\u03b6&gt;0$,":[231],"linear":[250],"or":[251],"Moreover,":[255],"simplify":[261],"strengthen":[263],"analysis":[265],"Chakraborty":[267],"et":[268],"al.,":[269],"obtaining":[270],"an":[271],"improved":[272],"1.968-approximation":[273],"setting.":[280]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-05-13T00:00:00"}
