{"id":"https://openalex.org/W2897148785","doi":"https://doi.org/10.1155/2018/7130146","title":"Deep Learning\u2010 and Word Embedding\u2010Based Heterogeneous Classifier Ensembles for Text Classification","display_name":"Deep Learning\u2010 and Word Embedding\u2010Based Heterogeneous Classifier Ensembles for Text Classification","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2897148785","doi":"https://doi.org/10.1155/2018/7130146","mag":"2897148785"},"language":"en","primary_location":{"id":"doi:10.1155/2018/7130146","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/7130146","pdf_url":"http://downloads.hindawi.com/journals/complexity/2018/7130146.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://downloads.hindawi.com/journals/complexity/2018/7130146.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060746555","display_name":"Zeynep Hilal Kilimci","orcid":"https://orcid.org/0000-0003-1497-305X"},"institutions":[{"id":"https://openalex.org/I129994210","display_name":"Do\u011fu\u015f University","ror":"https://ror.org/0272rjm42","country_code":"TR","type":"education","lineage":["https://openalex.org/I129994210"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Zeynep H. Kilimci","raw_affiliation_strings":["Computer Engineering Department, Dogus University, Istanbul 34722, Turkey","Computer Engineering Department, Dogus University, Istanbul 34722"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, Dogus University, Istanbul 34722, Turkey","institution_ids":["https://openalex.org/I129994210"]},{"raw_affiliation_string":"Computer Engineering Department, Dogus University, Istanbul 34722","institution_ids":["https://openalex.org/I129994210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089064593","display_name":"Selim Akyoku\u015f","orcid":"https://orcid.org/0000-0003-0793-1601"},"institutions":[{"id":"https://openalex.org/I3125470973","display_name":"Istanbul Medipol University","ror":"https://ror.org/037jwzz50","country_code":"TR","type":"education","lineage":["https://openalex.org/I3125470973"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Selim Akyokus","raw_affiliation_strings":["Computer Engineering Department, stanbul Medipol University, Istanbul 34722, Turkey","Computer Engineering Department, \u0130stanbul Medipol University, Istanbul 34722"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, stanbul Medipol University, Istanbul 34722, Turkey","institution_ids":["https://openalex.org/I3125470973"]},{"raw_affiliation_string":"Computer Engineering Department, \u0130stanbul Medipol University, Istanbul 34722","institution_ids":["https://openalex.org/I3125470973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060746555"],"corresponding_institution_ids":["https://openalex.org/I129994210"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":6.2613,"has_fulltext":true,"cited_by_count":93,"citation_normalized_percentile":{"value":0.97137848,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"2018","issue":"1","first_page":null,"last_page":null},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9983999729156494,"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/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7030923366546631},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6841873526573181},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6770439743995667},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6574516296386719},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5541804432868958},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4933740198612213},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4002973437309265},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14201760292053223}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7030923366546631},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6841873526573181},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6770439743995667},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6574516296386719},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5541804432868958},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4933740198612213},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4002973437309265},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14201760292053223},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2018/7130146","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/7130146","pdf_url":"http://downloads.hindawi.com/journals/complexity/2018/7130146.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:7130146","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/8503/2018/7130146.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"},{"id":"pmh:oai:doaj.org/article:9a0ec3102eff4a1889bbd82e65e4ffb4","is_oa":true,"landing_page_url":"https://doaj.org/article/9a0ec3102eff4a1889bbd82e65e4ffb4","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2018 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2018/7130146","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/7130146","pdf_url":"http://downloads.hindawi.com/journals/complexity/2018/7130146.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2897148785.pdf","grobid_xml":"https://content.openalex.org/works/W2897148785.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1496287430","https://openalex.org/W1697522679","https://openalex.org/W1800056794","https://openalex.org/W1826790618","https://openalex.org/W1832693441","https://openalex.org/W1963985812","https://openalex.org/W1989568037","https://openalex.org/W2006724638","https://openalex.org/W2023294425","https://openalex.org/W2038705219","https://openalex.org/W2076063813","https://openalex.org/W2112796928","https://openalex.org/W2118020653","https://openalex.org/W2120615054","https://openalex.org/W2139212933","https://openalex.org/W2141829097","https://openalex.org/W2149684865","https://openalex.org/W2152137105","https://openalex.org/W2155806188","https://openalex.org/W2167917621","https://openalex.org/W2222577885","https://openalex.org/W2244486986","https://openalex.org/W2250539671","https://openalex.org/W2307589391","https://openalex.org/W2317515691","https://openalex.org/W2320471648","https://openalex.org/W2523138083","https://openalex.org/W2604272474","https://openalex.org/W2604819731","https://openalex.org/W2743399036","https://openalex.org/W2802103240","https://openalex.org/W2806669038","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2963921497","https://openalex.org/W4205241946","https://openalex.org/W4240624099"],"related_works":["https://openalex.org/W947140380","https://openalex.org/W2296205523","https://openalex.org/W4286432911","https://openalex.org/W4230884544","https://openalex.org/W4245453790","https://openalex.org/W3194985222","https://openalex.org/W3216571906","https://openalex.org/W4214830338","https://openalex.org/W2518587255","https://openalex.org/W4287599800"],"abstract_inverted_index":{"The":[0,114],"use":[1,95],"of":[2,15,25,40,70,82,102,108,116,146,154,166,181],"ensemble":[3,107,115,153],"learning,":[4,6],"deep":[5,136,171],"and":[7,105,131,134,174],"effective":[8],"document":[9,97,148],"representation":[10,69],"methods":[11,50,173],"is":[12,32],"currently":[13],"some":[14],"the":[16,22,37,60,100,143,164,178],"most":[17],"common":[18],"trends":[19],"to":[20,35,87],"improve":[21],"overall":[23,38],"accuracy":[24,39,145],"a":[26,41,74,80,135],"text":[27,112],"classification/categorization":[28],"system.":[29],"Ensemble":[30],"learning":[31,64,122,172],"an":[33,106,152],"approach":[34],"raise":[36],"classification":[42,144,179],"system":[43],"by":[44,150],"utilizing":[45],"multiple":[46],"classifiers.":[47],"Deep":[48],"learning\u2010based":[49,137],"provide":[51,79],"better":[52],"results":[53,161],"in":[54],"many":[55],"applications":[56],"when":[57],"compared":[58],"with":[59,84,99,170],"other":[61],"conventional":[62,138],"machine":[63,121],"algorithms.":[65],"Word":[66],"embeddings":[67,104,176],"enable":[68],"words":[71,83],"learned":[72],"from":[73],"corpus":[75],"as":[76,125],"vectors":[77],"that":[78,163],"mapping":[81],"similar":[85,89],"meaning":[86],"have":[88],"representation.":[90],"In":[91],"this":[92],"study,":[93],"we":[94],"different":[96,147,158],"representations":[98,149],"benefit":[101],"word":[103,175],"base":[109,117],"classifiers":[110,118,155],"for":[111],"classification.":[113],"includes":[119],"traditional":[120],"algorithms":[123],"such":[124],"na\u00efve":[126],"Bayes,":[127],"support":[128],"vector":[129],"machine,":[130],"random":[132],"forest":[133],"network":[139],"classifier.":[140],"We":[141],"analysed":[142],"employing":[151],"on":[156],"eight":[157],"datasets.":[159],"Experimental":[160],"demonstrate":[162],"usage":[165],"heterogeneous":[167],"ensembles":[168],"together":[169],"enhances":[177],"performance":[180],"texts.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":8}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
