{"id":"https://openalex.org/W2995507664","doi":"https://doi.org/10.1109/ismsit.2019.8932767","title":"Extraction of Numerical data from Categorical Data Set and Artificial Neural Networks","display_name":"Extraction of Numerical data from Categorical Data Set and Artificial Neural Networks","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2995507664","doi":"https://doi.org/10.1109/ismsit.2019.8932767","mag":"2995507664"},"language":"en","primary_location":{"id":"doi:10.1109/ismsit.2019.8932767","doi":"https://doi.org/10.1109/ismsit.2019.8932767","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismsit.2019.8932767","pdf_url":null,"source":{"id":"https://openalex.org/S4363605511","display_name":"International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5015731717","display_name":"Ahmet H\u0131fz\u0131 Bacaks\u0131z","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmet Hifzi Bacaksiz","raw_affiliation_strings":["AI Birimi, MBIS Ar-Ge Merkezi, \u0130stanbul, T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Birimi, MBIS Ar-Ge Merkezi, \u0130stanbul, T\u00fcrkiye","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029312430","display_name":"Eren Esgin","orcid":"https://orcid.org/0000-0002-5454-4244","observed_orcids":["https://orcid.org/0000-0002-5454-4244"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eren Esgin","raw_affiliation_strings":["AI Birimi, MBIS Ar-Ge Merkezi, \u0130stanbul, T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Birimi, MBIS Ar-Ge Merkezi, \u0130stanbul, T\u00fcrkiye","institution_ids":[]}]}],"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":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12514462,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.3718000054359436,"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":0.3718000054359436,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.3330000042915344,"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/T10320","display_name":"Neural Networks and Applications","score":0.21699999272823334,"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/categorical-data","display_name":"categorical data","score":0.9020000100135803},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"multilayer perceptron","score":0.8740000128746033},{"id":"https://openalex.org/keywords/binary-transformation","display_name":"binary transformation","score":0.7039999961853027},{"id":"https://openalex.org/keywords/dimensional-reduction","display_name":"dimensional reduction","score":0.6700000166893005},{"id":"https://openalex.org/keywords/information-security","display_name":"information security","score":0.5260000228881836}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8367605805397034},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7531474828720093},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6705808639526367},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6096321940422058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5977344512939453},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5660766363143921},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47452059388160706},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.45843085646629333},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4468626379966736},{"id":"https://openalex.org/C2780365114","wikidata":"https://www.wikidata.org/wiki/Q169478","display_name":"MATLAB","level":2,"score":0.43582016229629517},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4328692853450775},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4275633692741394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4122031629085541},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1399633288383484},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ismsit.2019.8932767","doi":"https://doi.org/10.1109/ismsit.2019.8932767","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismsit.2019.8932767","pdf_url":null,"source":{"id":"https://openalex.org/S4363605511","display_name":"International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1196702536","https://openalex.org/W1879447438","https://openalex.org/W1961147827","https://openalex.org/W1991530504","https://openalex.org/W1992459313","https://openalex.org/W2003591606","https://openalex.org/W2270107170","https://openalex.org/W2270192120","https://openalex.org/W2598256660","https://openalex.org/W2605641866","https://openalex.org/W2753589683","https://openalex.org/W2891490729","https://openalex.org/W2900040601"],"related_works":["https://openalex.org/W2048461913","https://openalex.org/W3216112626","https://openalex.org/W4387000860","https://openalex.org/W4286849894","https://openalex.org/W4315777594","https://openalex.org/W4402979250","https://openalex.org/W4243358255","https://openalex.org/W4391106148","https://openalex.org/W2906705660","https://openalex.org/W2063300059"],"abstract_inverted_index":{"In":[0,18,159],"this":[1,130,160],"study,":[2,161],"the":[3,12,32,38,41,46,50,58,61,89,100,115,119,135,138,162,167,176],"need":[4],"for":[5,11],"numerical":[6,47],"data":[7,24,42,51,164,178,186],"which":[8,28],"is":[9,16,29,43,53,86,96,127,148,173],"required":[10],"machine":[13],"learning":[14],"techniques":[15],"considered.":[17],"order":[19],"to":[20,88,98],"classify":[21],"a":[22,80,83,93,123],"categorical":[23,56,90,120],"by":[25],"multilayer":[26,151],"perceptron,":[27],"one":[30],"of":[31,40,49,60,72,114,137,144,183],"well-known":[33],"artificial":[34],"neural":[35],"network":[36],"structure,":[37],"content":[39,52],"digitalized.":[44],"While":[45],"equivalent":[48],"created":[54],"at":[55,102,118],"level,":[57],"protection":[59],"information":[62],"it":[63],"carries":[64],"has":[65,77],"been":[66,78],"an":[67],"important":[68],"issue":[69],"in":[70,129,190],"terms":[71],"achieving":[73],"effective":[74],"results":[75,156],"and":[76,154,185,192],"studied":[79],"lot.":[81],"Here,":[82],"binary-defined":[84],"transformation":[85],"applied":[87],"data.":[91],"Afterwards,":[92],"guide":[94,108],"vector":[95,109],"implemented":[97,189],"protect":[99],"relation":[101,113],"its":[103],"own":[104],"business":[105],"context.":[106],"The":[107,141,180],"implicitly":[110],"conserves":[111],"positional":[112],"corresponding":[116],"dataset":[117,132],"level.":[121],"Hence,":[122],"significant":[124],"dimensional":[125],"reduction":[126],"accomplished":[128],"new":[131],"obtained":[133],"after":[134],"digitalization":[136],"original":[139],"dataset.":[140],"classification":[142],"performance":[143],"newly":[145],"extracted":[146,165],"features":[147],"validated":[149],"with":[150],"perceptron":[152],"structure":[153],"successful":[155],"are":[157,188],"observed.":[158],"actual":[163],"from":[166],"enterprise":[168],"resource":[169],"planning":[170],"(ERP)":[171],"system":[172],"used":[174],"as":[175],"main":[177],"source.":[179],"underlying":[181],"methods":[182],"modeling":[184],"processing":[187],"MATLAB":[191],"Python":[193],"programming":[194],"languages.":[195]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-12-26T00:00:00"}