{"id":"https://openalex.org/W3183911764","doi":"https://doi.org/10.1109/civemsa52099.2021.9493582","title":"Group Decision Making as Consistency Measure for Learning To Rank","display_name":"Group Decision Making as Consistency Measure for Learning To Rank","publication_year":2021,"publication_date":"2021-06-18","ids":{"openalex":"https://openalex.org/W3183911764","doi":"https://doi.org/10.1109/civemsa52099.2021.9493582","mag":"3183911764"},"language":"en","primary_location":{"id":"doi:10.1109/civemsa52099.2021.9493582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/civemsa52099.2021.9493582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","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/A5016277608","display_name":"Giuseppe Fenza","orcid":"https://orcid.org/0000-0002-4736-0113"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Giuseppe Fenza","raw_affiliation_strings":["University of Salerno, Fisciano (SA), Italy"],"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075091553","display_name":"Mariacristina Gallo","orcid":"https://orcid.org/0000-0002-5474-2697"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mariacristina Gallo","raw_affiliation_strings":["University of Salerno, Fisciano (SA), Italy"],"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036423849","display_name":"Vincenzo Loia","orcid":"https://orcid.org/0000-0003-4807-8942"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Vincenzo Loia","raw_affiliation_strings":["University of Salerno, Fisciano (SA), Italy"],"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077536249","display_name":"Francesco David Nota","orcid":"https://orcid.org/0000-0002-3380-0544"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco David Nota","raw_affiliation_strings":["University of Salerno, Fisciano (SA), Italy"],"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084287110","display_name":"Francesco Orciuoli","orcid":"https://orcid.org/0000-0001-6899-4396"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Orciuoli","raw_affiliation_strings":["University of Salerno, Fisciano (SA), Italy"],"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076657750","display_name":"Enrique Herrera\u2010Viedma","orcid":"https://orcid.org/0000-0002-7922-4984"},"institutions":[{"id":"https://openalex.org/I4210095677","display_name":"Instituto Andaluz de Ciencias de la Tierra","ror":"https://ror.org/00v0g9w49","country_code":"ES","type":"facility","lineage":["https://openalex.org/I134820265","https://openalex.org/I4210095677"]},{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Enrique Herrera-Viedma","raw_affiliation_strings":["Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, Granada, Spain"],"affiliations":[{"raw_affiliation_string":"Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, Granada, Spain","institution_ids":["https://openalex.org/I4210095677","https://openalex.org/I173304897"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5016277608"],"corresponding_institution_ids":["https://openalex.org/I131729948"],"apc_list":null,"apc_paid":null,"fwci":0.3486,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.62270639,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9939000010490417,"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"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9939000010490417,"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"}},{"id":"https://openalex.org/T10050","display_name":"Multi-Criteria Decision Making","score":0.9894999861717224,"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"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9876000285148621,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7939016819000244},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7097455859184265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6870770454406738},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6518133878707886},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.588372528553009},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5850499868392944},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.5157566070556641},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5123306512832642},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.485299289226532},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.45355233550071716},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3015361726284027},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19833391904830933},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17387330532073975}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7939016819000244},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7097455859184265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6870770454406738},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6518133878707886},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.588372528553009},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5850499868392944},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.5157566070556641},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5123306512832642},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.485299289226532},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.45355233550071716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3015361726284027},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19833391904830933},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17387330532073975},{"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:10.1109/civemsa52099.2021.9493582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/civemsa52099.2021.9493582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W601033028","https://openalex.org/W1574447377","https://openalex.org/W1973435495","https://openalex.org/W1985514943","https://openalex.org/W2069870183","https://openalex.org/W2072128103","https://openalex.org/W2137479650","https://openalex.org/W2138962584","https://openalex.org/W2169038408","https://openalex.org/W2195118355","https://openalex.org/W2252909801","https://openalex.org/W2304548633","https://openalex.org/W2626639386","https://openalex.org/W2725795733","https://openalex.org/W2739345445","https://openalex.org/W2805619469","https://openalex.org/W2884090605","https://openalex.org/W2928069584","https://openalex.org/W2953271441","https://openalex.org/W2963483561","https://openalex.org/W2963749936","https://openalex.org/W2963798744","https://openalex.org/W4239181501","https://openalex.org/W4293861706","https://openalex.org/W4302313152","https://openalex.org/W6739575509","https://openalex.org/W6750391026","https://openalex.org/W6761206467"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W1546381263","https://openalex.org/W3160516639","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2922169395"],"abstract_inverted_index":{"Quality":[0],"of":[1,10,14,16,31,81,96],"training":[2,32,121],"data":[3,33,117],"deeply":[4],"influences":[5],"Machine":[6],"Learning":[7,45],"performance.":[8,112],"Lack":[9],"consistency":[11,34,53,76],"in":[12,64],"terms":[13],"coherence":[15],"labels":[17],"for":[18,35],"similar":[19],"items":[20],"can":[21],"mislead":[22],"the":[23,29,44,59,70,74,79,94,97,120],"learning":[24,37,110],"model.":[25],"This":[26],"work":[27],"studies":[28],"role":[30],"machine":[36],"algorithms":[38],"dealing":[39],"with":[40],"ranking":[41],"problems,":[42],"i.e.,":[43],"to":[46],"Rank":[47],"(LTR)":[48],"methods.":[49],"In":[50],"particular,":[51],"a":[52,82,102],"measure":[54,77,99],"is":[55,90],"introduced":[56],"by":[57],"leveraging":[58],"consensus":[60,107],"value":[61],"broadly":[62],"adopted":[63],"Group":[65],"Decision":[66],"Making":[67],"(GDM).":[68],"Then,":[69],"statistical":[71],"relationship":[72],"between":[73,105],"proposed":[75,98],"and":[78,100,108,123],"performance":[80],"deep":[83,109],"neural":[84],"network":[85],"implementing":[86],"an":[87],"LTR":[88],"method":[89],"evaluated.":[91],"Experimentation":[92],"confirms":[93],"suitability":[95],"reveals":[101],"heavy":[103],"correlation":[104],"GDM":[106],"model":[111,125],"Such":[113],"information":[114],"could":[115],"drive":[116],"filtering":[118],"at":[119],"stage":[122],"guide":[124],"update":[126],"decisions.":[127]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
