{"id":"https://openalex.org/W3036069605","doi":"https://doi.org/10.1177/0165551520930897","title":"The effects of globalisation techniques on feature selection for text classification","display_name":"The effects of globalisation techniques on feature selection for text classification","publication_year":2020,"publication_date":"2020-06-18","ids":{"openalex":"https://openalex.org/W3036069605","doi":"https://doi.org/10.1177/0165551520930897","mag":"3036069605"},"language":"en","primary_location":{"id":"doi:10.1177/0165551520930897","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0165551520930897","pdf_url":null,"source":{"id":"https://openalex.org/S68913162","display_name":"Journal of Information Science","issn_l":"0165-5515","issn":["0165-5515","1741-6485"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information Science","raw_type":"journal-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/A5103175156","display_name":"Bekir Parlak","orcid":"https://orcid.org/0000-0001-8919-6481"},"institutions":[{"id":"https://openalex.org/I4210091955","display_name":"Eskisehir Technical University","ror":"https://ror.org/00gcgqv39","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210091955"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Bekir Parlak","raw_affiliation_strings":["Department of Computer Engineering, Faculty of Engineering, Eski\u015fehir Technical University, Turkey"],"raw_orcid":"https://orcid.org/0000-0001-8919-6481","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Faculty of Engineering, Eski\u015fehir Technical University, Turkey","institution_ids":["https://openalex.org/I4210091955"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060591593","display_name":"Alper K\u00fcr\u015fat Uysal","orcid":"https://orcid.org/0000-0002-4057-934X"},"institutions":[{"id":"https://openalex.org/I4210091955","display_name":"Eskisehir Technical University","ror":"https://ror.org/00gcgqv39","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210091955"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Alper Kursat Uysal","raw_affiliation_strings":["Department of Computer Engineering, Faculty of Engineering, Eski\u015fehir Technical University, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Faculty of Engineering, Eski\u015fehir Technical University, Turkey","institution_ids":["https://openalex.org/I4210091955"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103175156"],"corresponding_institution_ids":["https://openalex.org/I4210091955"],"apc_list":null,"apc_paid":null,"fwci":2.0401,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.8952283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"47","issue":"6","first_page":"727","last_page":"739"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9998000264167786,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9998000264167786,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9898999929428101,"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/computer-science","display_name":"Computer science","score":0.7006916403770447},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6825507879257202},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6640158295631409},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6263364553451538},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.574222207069397},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5261958241462708},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5024936199188232},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47273436188697815},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4110783338546753}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7006916403770447},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6825507879257202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6640158295631409},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6263364553451538},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.574222207069397},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5261958241462708},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5024936199188232},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47273436188697815},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4110783338546753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1177/0165551520930897","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0165551520930897","pdf_url":null,"source":{"id":"https://openalex.org/S68913162","display_name":"Journal of Information Science","issn_l":"0165-5515","issn":["0165-5515","1741-6485"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information Science","raw_type":"journal-article"},{"id":"pmh:1127b049-ec57-4b1f-b1b1-5b00bcf203b3","is_oa":false,"landing_page_url":"https://avesis.comu.edu.tr/publication/details/1127b049-ec57-4b1f-b1b1-5b00bcf203b3/oai","pdf_url":null,"source":{"id":"https://openalex.org/S7407055198","display_name":"\u00c7anakkale Onsekiz Mart University AVESIS","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1426199569","https://openalex.org/W1826790618","https://openalex.org/W1973637371","https://openalex.org/W1980229662","https://openalex.org/W1987504723","https://openalex.org/W2075688077","https://openalex.org/W2090702536","https://openalex.org/W2092782467","https://openalex.org/W2103333826","https://openalex.org/W2108150588","https://openalex.org/W2118020653","https://openalex.org/W2134090438","https://openalex.org/W2343999414","https://openalex.org/W2602655087","https://openalex.org/W2738417325","https://openalex.org/W2766554185","https://openalex.org/W2774057992","https://openalex.org/W2884353925","https://openalex.org/W2900990371","https://openalex.org/W2936210189","https://openalex.org/W3147409145","https://openalex.org/W4235486249","https://openalex.org/W4247582552","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2510961579","https://openalex.org/W1487808658"],"abstract_inverted_index":{"Text":[0],"classification":[1],"(TC)":[2],"is":[3,52,174,190],"very":[4],"important":[5,50],"and":[6,45,92,108,132,150,159,195,202,213,220],"critical":[7],"task":[8],"in":[9,100,152,231],"the":[10,22,48,64,113,136,166,169],"21th":[11],"century":[12],"as":[13,82,124,146],"there":[14],"exist":[15],"high":[16],"volume":[17],"of":[18,34,42,47,66,115],"electronic":[19],"data":[20,27],"on":[21,70,198,216],"Internet.":[23],"In":[24,57,135],"TC,":[25],"textual":[26],"are":[28,103,179],"characterised":[29],"by":[30],"a":[31],"huge":[32],"number":[33],"highly":[35],"sparse":[36],"features/terms.":[37],"A":[38],"typical":[39],"TC":[40],"consists":[41],"many":[43],"steps":[44,51],"one":[46],"most":[49,170,232],"undoubtedly":[53],"feature":[54,72],"selection":[55,73],"(FS).":[56],"this":[58,101],"study,":[59],"we":[60,118,138],"have":[61,139],"comprehensively":[62],"investigated":[63],"effects":[65],"various":[67],"globalisation":[68,97,116,172],"techniques":[69,98],"local":[71],"(LFS)":[74],"methods":[75,122,197,215],"using":[76],"datasets":[77,144,199,217],"with":[78,200,218],"different":[79,142],"characteristics":[80],"such":[81],"multi-class":[83,86],"unbalanced":[84,90],"(MCU),":[85],"balanced":[87,94],"(MCB),":[88],"binary-class":[89,93],"(BCU)":[91],"(BCB).":[95],"The":[96,183],"used":[99,119],"study":[102],"summation":[104],"(SUM),":[105],"weighted-sum":[106],"(AVG),":[107],"maximum":[109],"(MAX).":[110],"To":[111],"investigate":[112],"effect":[114],"techniques,":[117],"three":[120],"LFS":[121],"named":[123,145],"Discriminative":[125],"Feature":[126],"Selection":[127],"(DFSS),":[128],"odds":[129],"ratio":[130],"(OR)":[131],"chi-square":[133],"(CHI2).":[134],"experiments,":[137],"utilised":[140],"four":[141],"benchmark":[143],"Reuters-21578,":[147],"20Newsgroup.,":[148],"Enron1,":[149],"Polarity":[151],"addition":[153],"to":[154,165],"Support":[155],"Vector":[156],"Machines":[157],"(SVM)":[158],"Decision":[160],"Tree":[161],"(DT)":[162],"classifiers.":[163],"According":[164],"experimental":[167,184],"results,":[168],"successful":[171,192],"technique":[173],"AVG":[175],"while":[176],"all":[177],"situations":[178],"taken":[180],"into":[181],"account.":[182],"results":[185],"indicate":[186],"that":[187],"DFSS":[188,214],"method":[189,207],"more":[191,209],"than":[193,211,228],"OR":[194,212],"CHI2":[196,206],"MCU":[201],"MCB":[203],"characteristics.":[204,222],"However,":[205],"seems":[208],"accurate":[210],"BCU":[219],"BCB":[221],"Also,":[223],"SVM":[224],"classifier":[225,230],"performed":[226],"better":[227],"DT":[229],"cases.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}