{"id":"https://openalex.org/W1974334076","doi":"https://doi.org/10.1109/fuzz-ieee.2013.6622376","title":"OWA aggregation of fuzzy similarity relations for journal ranking","display_name":"OWA aggregation of fuzzy similarity relations for journal ranking","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W1974334076","doi":"https://doi.org/10.1109/fuzz-ieee.2013.6622376","mag":"1974334076"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2013.6622376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2013.6622376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5052907741","display_name":"Su Pan","orcid":"https://orcid.org/0000-0002-0590-9227"},"institutions":[{"id":"https://openalex.org/I16038530","display_name":"Aberystwyth University","ror":"https://ror.org/015m2p889","country_code":"GB","type":"education","lineage":["https://openalex.org/I16038530"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Pan Su","raw_affiliation_strings":["Department of Computer Science, Aberystwyth University, Aberystwyth, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aberystwyth University, Aberystwyth, UK","institution_ids":["https://openalex.org/I16038530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039652471","display_name":"Changjing Shang","orcid":"https://orcid.org/0000-0001-6375-6276"},"institutions":[{"id":"https://openalex.org/I16038530","display_name":"Aberystwyth University","ror":"https://ror.org/015m2p889","country_code":"GB","type":"education","lineage":["https://openalex.org/I16038530"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Changjing Shang","raw_affiliation_strings":["Department of Computer Science, Aberystwyth University, Aberystwyth, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aberystwyth University, Aberystwyth, UK","institution_ids":["https://openalex.org/I16038530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036010787","display_name":"Qiang Shen","orcid":"https://orcid.org/0000-0001-9333-4605"},"institutions":[{"id":"https://openalex.org/I16038530","display_name":"Aberystwyth University","ror":"https://ror.org/015m2p889","country_code":"GB","type":"education","lineage":["https://openalex.org/I16038530"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Qiang Shen","raw_affiliation_strings":["Department of Computer Science, Aberystwyth University, Aberystwyth, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aberystwyth University, Aberystwyth, UK","institution_ids":["https://openalex.org/I16038530"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052907741"],"corresponding_institution_ids":["https://openalex.org/I16038530"],"apc_list":null,"apc_paid":null,"fwci":2.2441,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.87613365,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9901999831199646,"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":0.9901999831199646,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9879999756813049,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9872000217437744,"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/weighting","display_name":"Weighting","score":0.7934773564338684},{"id":"https://openalex.org/keywords/transitive-relation","display_name":"Transitive relation","score":0.7590813636779785},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7281438112258911},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6832560300827026},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5761838555335999},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5462020635604858},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5362690091133118},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5092469453811646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47852930426597595},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.44963783025741577},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.43326759338378906},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.43301212787628174},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4286859929561615},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.42448610067367554},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3258455991744995},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09792980551719666}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7934773564338684},{"id":"https://openalex.org/C191399111","wikidata":"https://www.wikidata.org/wiki/Q64861","display_name":"Transitive relation","level":2,"score":0.7590813636779785},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7281438112258911},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6832560300827026},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5761838555335999},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5462020635604858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5362690091133118},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5092469453811646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47852930426597595},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.44963783025741577},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.43326759338378906},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.43301212787628174},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4286859929561615},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.42448610067367554},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3258455991744995},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09792980551719666},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"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/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2013.6622376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2013.6622376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W104074713","https://openalex.org/W1503428008","https://openalex.org/W1505519009","https://openalex.org/W1509414391","https://openalex.org/W1714190850","https://openalex.org/W1958739611","https://openalex.org/W1980317569","https://openalex.org/W1982618675","https://openalex.org/W1992419399","https://openalex.org/W1994387177","https://openalex.org/W2009550727","https://openalex.org/W2016461138","https://openalex.org/W2019529630","https://openalex.org/W2035518679","https://openalex.org/W2038105248","https://openalex.org/W2038745769","https://openalex.org/W2060907774","https://openalex.org/W2078225063","https://openalex.org/W2080152553","https://openalex.org/W2099167966","https://openalex.org/W2105771677","https://openalex.org/W2108927591","https://openalex.org/W2109068396","https://openalex.org/W2119876047","https://openalex.org/W2124201070","https://openalex.org/W2124232882","https://openalex.org/W2126848313","https://openalex.org/W2132631086","https://openalex.org/W2153734213","https://openalex.org/W2168190036","https://openalex.org/W2207899741","https://openalex.org/W2394927731","https://openalex.org/W3140407031","https://openalex.org/W6604230859","https://openalex.org/W6630038387","https://openalex.org/W6630231347"],"related_works":["https://openalex.org/W4312527695","https://openalex.org/W2361167282","https://openalex.org/W1528932152","https://openalex.org/W2180954594","https://openalex.org/W2091342995","https://openalex.org/W2271118953","https://openalex.org/W3007067598","https://openalex.org/W2052835778","https://openalex.org/W2359420171","https://openalex.org/W1677394555"],"abstract_inverted_index":{"Fuzzy":[0],"similarity":[1,17,61,97],"relations":[2,32],"form":[3],"the":[4,22,69,72,105,115,152],"basis":[5],"for":[6,24,104],"many":[7],"developments":[8],"and":[9,84,99,144,158],"applications":[10],"of":[11,15,71,107,117,122,141,154],"fuzzy":[12,16,31,60],"systems.":[13],"Measures":[14],"have":[18],"been":[19],"proposed":[20,79,148],"in":[21,110,139],"literature":[23],"comparing":[25],"objects.":[26],"In":[27,49],"this":[28],"paper,":[29],"aggregated":[30,80],"are":[33,94,102],"generated":[34],"between":[35],"academic":[36,118],"journals":[37],"to":[38,44,56,113],"compare":[39],"their":[40],"performance":[41],"with":[42,86],"respect":[43],"different":[45],"journal":[46,108],"impact":[47],"indicators.":[48],"particular,":[50],"various":[51],"indicators":[52],"may":[53,64],"be":[54,65],"employed":[55],"construct":[57],"several":[58],"distinctive":[59],"relations,":[62,130],"which":[63],"subsequently":[66],"combined":[67],"via":[68],"use":[70],"Ordered":[73],"Weighted":[74],"Average":[75],"(OWA)":[76],"operator.":[77],"This":[78],"measure":[81],"preserves":[82],"reflexivity":[83],"symmetry,":[85],"T-transitivity":[87],"conditionally":[88],"preserved":[89],"if":[90],"appropriate":[91],"weighting":[92,100],"vectors":[93,101],"selected.":[95],"Different":[96],"measures":[98],"compared":[103],"task":[106],"clustering,":[109],"an":[111],"effort":[112],"estimate":[114],"ranking":[116],"journals.":[119],"The":[120,147],"results":[121],"experimental":[123],"evaluation":[124],"demonstrate":[125],"that":[126],"by":[127],"using":[128],"OWA-aggregated":[129],"simple":[131],"techniques":[132],"such":[133],"as":[134],"C-means":[135],"can":[136],"perform":[137],"well":[138],"terms":[140],"standard":[142],"accuracy":[143],"within-1":[145],"accuracy.":[146],"method":[149],"also":[150],"exhibits":[151],"advantages":[153],"being":[155],"more":[156],"intuitive":[157],"interpretable.":[159]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
