{"id":"https://openalex.org/W2977019202","doi":"https://doi.org/10.1145/3341981.3344246","title":"Generalising Kendall's Tau for Noisy and Incomplete Preference Judgements","display_name":"Generalising Kendall's Tau for Noisy and Incomplete Preference Judgements","publication_year":2019,"publication_date":"2019-09-26","ids":{"openalex":"https://openalex.org/W2977019202","doi":"https://doi.org/10.1145/3341981.3344246","mag":"2977019202"},"language":"en","primary_location":{"id":"doi:10.1145/3341981.3344246","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341981.3344246","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM SIGIR International Conference on Theory of 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/A5006505274","display_name":"Riku Togashi","orcid":"https://orcid.org/0000-0001-9026-0495"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Riku Togashi","raw_affiliation_strings":["Mercari Inc. &amp; Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Mercari Inc. &amp; Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023595778","display_name":"Tetsuya Sakai","orcid":"https://orcid.org/0000-0002-6720-963X"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Sakai","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006505274"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.1659,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45212962,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"193","last_page":"196"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9980999827384949,"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"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9916999936103821,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.8571559190750122},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7787659168243408},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.7201034426689148},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6438344120979309},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6070297956466675},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6051164865493774},{"id":"https://openalex.org/keywords/preference-learning","display_name":"Preference learning","score":0.5927902460098267},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5706570744514465},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.5529963970184326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5288463830947876},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4235967993736267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41619983315467834},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.41357845067977905},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3526693284511566},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2714919447898865},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2616650462150574},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23564547300338745}],"concepts":[{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.8571559190750122},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7787659168243408},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.7201034426689148},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6438344120979309},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6070297956466675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6051164865493774},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.5927902460098267},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5706570744514465},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.5529963970184326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5288463830947876},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4235967993736267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41619983315467834},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.41357845067977905},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3526693284511566},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2714919447898865},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2616650462150574},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23564547300338745},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3341981.3344246","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341981.3344246","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5099999904632568,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1556861584","https://openalex.org/W1966835268","https://openalex.org/W2021581601","https://openalex.org/W2051752522","https://openalex.org/W2160637580","https://openalex.org/W2760642188","https://openalex.org/W2763110165","https://openalex.org/W2923225236"],"related_works":["https://openalex.org/W2931602588","https://openalex.org/W2937325523","https://openalex.org/W1986265453","https://openalex.org/W3160516639","https://openalex.org/W4403346496","https://openalex.org/W4205377104","https://openalex.org/W257970033","https://openalex.org/W1994181006","https://openalex.org/W2911102221","https://openalex.org/W2943672508"],"abstract_inverted_index":{"We":[0,119],"propose":[1,166],"a":[2,95,111,116,194],"new":[3],"ranking":[4,168],"evaluation":[5,169],"measure":[6,170],"for":[7,15,41,59,115,133],"situations":[8,122],"where":[9,123],"multiple":[10,124],"preference":[11,45,57,78,125,129,144],"judgements":[12,26,33,46,58,79],"are":[13,27,34,131],"given":[14,117,132],"each":[16,106,134],"item":[17],"pair":[18],"but":[19],"they":[20],"may":[21],"be":[22,68,85],"noisy":[23,75],"(i.e.,":[24,31],"some":[25,32],"unreliable)":[28],"and/or":[29],"incomplete":[30,77],"missing).":[35],"While":[36],"it":[37,50],"is":[38,51,92,108],"generally":[39],"easier":[40],"assessors":[42],"to":[43,55,149,157],"conduct":[44],"than":[47,128,191],"absolute":[48],"judgements,":[49,145],"often":[52],"not":[53],"practical":[54],"obtain":[56,158],"all":[60],"combinations":[61],"of":[62,100,142,153],"documents.":[63],"However,":[64],"this":[65,163],"problem":[66],"can":[67,72,84,186],"overcome":[69],"if":[70],"we":[71,165,177],"effectively":[73],"utilise":[74],"and":[76,184],"such":[80,159],"as":[81],"those":[82],"that":[83,105,179],"obtained":[86],"from":[87],"crowdsourcing.":[88],"Our":[89],"measure,":[90],"\u03b7,":[91],"based":[93],"on":[94],"simple":[96],"probabilistic":[97],"user":[98],"model":[99],"the":[101,140],"labellers":[102],"which":[103],"assumes":[104],"document":[107,135],"associated":[109],"with":[110],"graded":[112],"relevance":[113],"score":[114],"query.":[118],"also":[120],"consider":[121],"probabilities,":[126],"rather":[127],"labels,":[130],"pair.":[136],"For":[137,162],"example,":[138],"in":[139],"absence":[141],"manual":[143],"one":[146],"might":[147],"want":[148],"employ":[150],"an":[151],"ensemble":[152],"machine":[154],"learning":[155],"techniques":[156],"estimated":[160],"probabilities.":[161],"scenario,":[164],"another":[167],"called":[171],"\u03b7_p":[172],"$.":[173],"Through":[174],"simulated":[175],"experiments,":[176],"demonstrate":[178],"our":[180],"proposed":[181],"measures":[182],"\u03b7":[183],"\u03b7_p$":[185],"evaluate":[187],"rankings":[188],"more":[189],"reliably":[190],"\u03c4\\mbox-":[192],"b$,":[193],"popular":[195],"rank":[196],"correlation":[197],"measure.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
