{"id":"https://openalex.org/W7202292587","doi":"https://doi.org/10.1109/edm69524.2026.11632045","title":"Automatic Routing of Official Documents Entering the Organization\u2019s Executive System Based on NLP Transformer Models and Semantic Segmentation","display_name":"Automatic Routing of Official Documents Entering the Organization\u2019s Executive System Based on NLP Transformer Models and Semantic Segmentation","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7202292587","doi":"https://doi.org/10.1109/edm69524.2026.11632045"},"language":"en","primary_location":{"id":"doi:10.1109/edm69524.2026.11632045","doi":"https://doi.org/10.1109/edm69524.2026.11632045","is_oa":true,"landing_page_url":"https://doi.org/10.1109/edm69524.2026.11632045","pdf_url":null,"source":{"id":"https://openalex.org/S4210202527","display_name":"International Siberian workshops and tutorials on electron devices and materials","issn_l":"1815-3712","issn":["1815-3712"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 27th International Conference of Young Professionals in Electron Devices and Materials (EDM)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/edm69524.2026.11632045","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120847729","display_name":"Saidbek Babayazov","orcid":"https://orcid.org/0009-0003-7599-824X","observed_orcids":["https://orcid.org/0009-0003-7599-824X"]},"institutions":[{"id":"https://openalex.org/I207169309","display_name":"Cyber University","ror":"https://ror.org/038sdcw17","country_code":"JP","type":"education","lineage":["https://openalex.org/I207169309"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Saidbek Babayazov","raw_affiliation_strings":["Cyber University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cyber University","institution_ids":["https://openalex.org/I207169309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136583535","display_name":"Gavkhar Zokir qizi Nayimova","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I207169309","display_name":"Cyber University","ror":"https://ror.org/038sdcw17","country_code":"JP","type":"education","lineage":["https://openalex.org/I207169309"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gavkhar Nayimova","raw_affiliation_strings":["Cyber University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cyber University","institution_ids":["https://openalex.org/I207169309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137634077","display_name":"Mehrangiz Murodova","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I207169309","display_name":"Cyber University","ror":"https://ror.org/038sdcw17","country_code":"JP","type":"education","lineage":["https://openalex.org/I207169309"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mehrangiz Murodova","raw_affiliation_strings":["Cyber University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cyber University","institution_ids":["https://openalex.org/I207169309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058644301","display_name":"\u0410\u0431\u0434\u0443\u0432\u0430\u043b\u0438\u0435\u0432\u0430 \u0417\u0435\u0431\u0438\u043d\u0438\u0441\u043e \u0410\u0431\u0434\u0443\u043b\u0445\u0430\u043c\u0438\u0434\u043e\u0432\u043d\u0430","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I21256249","display_name":"Tashkent University of Information Technology","ror":"https://ror.org/05987a729","country_code":"UZ","type":"education","lineage":["https://openalex.org/I21256249"]}],"countries":["UZ"],"is_corresponding":false,"raw_author_name":"Zebiniso Abduvaliyeva","raw_affiliation_strings":["Tashkent University of Information Technologies named after Muhammad al-Khwarizmi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tashkent University of Information Technologies named after Muhammad al-Khwarizmi","institution_ids":["https://openalex.org/I21256249"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119253151","display_name":"Muborak Matyakubova","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I14916453","display_name":"Urgench State University","ror":"https://ror.org/0593kfr97","country_code":"UZ","type":"education","lineage":["https://openalex.org/I14916453"]}],"countries":["UZ"],"is_corresponding":false,"raw_author_name":"Muborak Matyakubova","raw_affiliation_strings":["Urgench State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Urgench State University","institution_ids":["https://openalex.org/I14916453"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5099060189","display_name":"Mohira MATNAZAROVA","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I14916453","display_name":"Urgench State University","ror":"https://ror.org/0593kfr97","country_code":"UZ","type":"education","lineage":["https://openalex.org/I14916453"]}],"countries":["UZ"],"is_corresponding":false,"raw_author_name":"Matnazarova Mohira","raw_affiliation_strings":["Urgench State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Urgench State University","institution_ids":["https://openalex.org/I14916453"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.8574000000953674,"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":0.8574000000953674,"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":0.13019999861717224,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.004600000102072954,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/government-documents","display_name":"government documents","score":0.9850000143051147},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":0.6110000014305115},{"id":"https://openalex.org/keywords/transformer","display_name":"transformer models","score":0.8880000114440918},{"id":"https://openalex.org/keywords/bert","display_name":"BERT","score":0.9100000262260437},{"id":"https://openalex.org/keywords/document-classification","display_name":"document classification","score":0.7179999947547913},{"id":"https://openalex.org/keywords/document-flow","display_name":"document flow","score":0.4059999883174896},{"id":"https://openalex.org/keywords/lda","display_name":"LDA","score":0.6470000147819519},{"id":"https://openalex.org/keywords/government-document-management","display_name":"government document management","score":0.3869999945163727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7103999853134155},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5529999732971191},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5489000082015991},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5335000157356262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5060999989509583},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33709999918937683},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3089999854564667},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.2513999938964844},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24959999322891235},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.24899999797344208}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/edm69524.2026.11632045","doi":"https://doi.org/10.1109/edm69524.2026.11632045","is_oa":true,"landing_page_url":"https://doi.org/10.1109/edm69524.2026.11632045","pdf_url":null,"source":{"id":"https://openalex.org/S4210202527","display_name":"International Siberian workshops and tutorials on electron devices and materials","issn_l":"1815-3712","issn":["1815-3712"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 27th International Conference of Young Professionals in Electron Devices and Materials (EDM)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/edm69524.2026.11632045","doi":"https://doi.org/10.1109/edm69524.2026.11632045","is_oa":true,"landing_page_url":"https://doi.org/10.1109/edm69524.2026.11632045","pdf_url":null,"source":{"id":"https://openalex.org/S4210202527","display_name":"International Siberian workshops and tutorials on electron devices and materials","issn_l":"1815-3712","issn":["1815-3712"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 27th International Conference of Young Professionals in Electron Devices and Materials (EDM)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.428600013256073}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1880262756","https://openalex.org/W4379519265","https://openalex.org/W4390013088","https://openalex.org/W4404790409","https://openalex.org/W4404790645","https://openalex.org/W4405786767","https://openalex.org/W4405786784","https://openalex.org/W4411864183","https://openalex.org/W4417471368","https://openalex.org/W4417472462"],"related_works":["https://openalex.org/W7166556161","https://openalex.org/W7200452330","https://openalex.org/W3027925036","https://openalex.org/W7130598301","https://openalex.org/W2897626622","https://openalex.org/W7017721916","https://openalex.org/W4387773715","https://openalex.org/W7167607543","https://openalex.org/W6992723003","https://openalex.org/W7202296882"],"abstract_inverted_index":{"The":[0,65,117,184,208],"rapid":[1],"growth":[2],"of":[3,19,58,71,121,171],"document":[4,27,202,225],"flow":[5],"in":[6,13,61,204,214],"organizational":[7,62],"execution":[8,63,205,229],"systems":[9],"creates":[10],"significant":[11],"challenges":[12],"the":[14,101,143,161],"timely":[15],"and":[16,42,56,81,96,142,154,178,197,220,228],"accurate":[17],"routing":[18,57,203],"official":[20,59,123],"documents":[21,60,72],"to":[22,34,77,108,174,223],"responsible":[23],"departments.":[24],"A":[25],"single":[26],"often":[28],"contains":[29],"multiple":[30],"thematic":[31],"segments":[32],"related":[33],"different":[35],"structural":[36],"units,":[37],"which":[38,92,125],"complicates":[39],"manual":[40],"processing":[41,226],"reduces":[43],"operational":[44],"efficiency.":[45],"This":[46],"study":[47],"proposes":[48],"an":[49,169,195],"artificial":[50],"intelligence-based":[51],"algorithm":[52],"for":[53,176,180,200],"automatic":[54],"classification":[55,79],"systems.":[64,207],"proposed":[66,102,144,162,209],"approach":[67,163,210],"combines":[68],"semantic":[69,132,188],"segmentation":[70,189],"with":[73,113,191],"transformer-based":[74],"text":[75],"embeddings":[76],"improve":[78,224],"accuracy":[80],"contextual":[82],"understanding.":[83],"Unlike":[84],"classical":[85,166],"topic":[86],"modeling":[87],"methods":[88],"such":[89],"as":[90],"LDA,":[91],"require":[93],"large":[94,221],"corpora":[95],"demonstrate":[97,159],"limited":[98],"generalization":[99],"capabilities,":[100],"method":[103],"leverages":[104],"pre-trained":[105],"transformer":[106,192],"models":[107,135,193],"achieve":[109],"high":[110],"performance":[111],"even":[112],"a":[114],"moderate-sized":[115],"dataset.":[116],"experimental":[118],"dataset":[119],"consisted":[120],"200":[122],"documents,":[124],"were":[126,136],"segmented":[127],"into":[128],"more":[129],"than":[130],"1,200":[131],"fragments.":[133],"Three":[134],"evaluated:":[137],"LDA":[138,177],"(baseline),":[139],"BERT-based":[140],"classification,":[141],"segmentationenhanced":[145],"BERT":[146,182],"model.":[147],"Performance":[148],"was":[149],"assessed":[150],"using":[151],"Precision,":[152],"Recall,":[153],"F1-score":[155,170],"metrics.":[156],"Experimental":[157],"results":[158],"that":[160,187],"significantly":[164],"outperforms":[165],"methods,":[167],"achieving":[168],"0.91":[172],"compared":[173],"0.50":[175],"0.84":[179],"standard":[181],"classification.":[183],"findings":[185],"confirm":[186],"combined":[190],"provides":[194],"effective":[196],"scalable":[198],"solution":[199],"intelligent":[201],"management":[206],"can":[211],"be":[212],"applied":[213],"governmental":[215],"institutions,":[216,219],"higher":[217],"education":[218],"organizations":[222],"efficiency":[227],"discipline.":[230]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-08-13T00:00:00"}
