{"id":"https://openalex.org/W4414809526","doi":"https://doi.org/10.1002/itl2.70153","title":"Intelligent English Teaching Video Traffic Classification in Wireless Communication Networks via Large Model\u2010Enhanced Sparse Attention Vision Transformer","display_name":"Intelligent English Teaching Video Traffic Classification in Wireless Communication Networks via Large Model\u2010Enhanced Sparse Attention Vision Transformer","publication_year":2025,"publication_date":"2025-10-04","ids":{"openalex":"https://openalex.org/W4414809526","doi":"https://doi.org/10.1002/itl2.70153"},"language":"en","primary_location":{"id":"doi:10.1002/itl2.70153","is_oa":false,"landing_page_url":"https://doi.org/10.1002/itl2.70153","pdf_url":null,"source":{"id":"https://openalex.org/S4210238311","display_name":"Internet Technology Letters","issn_l":"2476-1508","issn":["2476-1508"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Internet Technology Letters","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/A5029030736","display_name":"Jinjin Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I92092256","display_name":"Huanghe Science and Technology College","ror":"https://ror.org/008p6rr25","country_code":"CN","type":"education","lineage":["https://openalex.org/I92092256"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinjin Liu","raw_affiliation_strings":["Huanghe University of Science and Technology  Zhengzhou People's Republic of China","Huanghe University of Science and Technology, Zhengzhou, People's Republic of China"],"affiliations":[{"raw_affiliation_string":"Huanghe University of Science and Technology  Zhengzhou People's Republic of China","institution_ids":["https://openalex.org/I92092256"]},{"raw_affiliation_string":"Huanghe University of Science and Technology, Zhengzhou, People's Republic of China","institution_ids":["https://openalex.org/I92092256"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5029030736"],"corresponding_institution_ids":["https://openalex.org/I92092256"],"apc_list":{"value":2630,"currency":"USD","value_usd":2630},"apc_paid":null,"fwci":1.2826,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.84823652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":"6","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9750999808311462,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9750999808311462,"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"}},{"id":"https://openalex.org/T13073","display_name":"China's Ethnic Minorities and Relations","score":0.9736999869346619,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9435999989509583,"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/transformer","display_name":"Transformer","score":0.6601999998092651},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.6340000033378601},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4973999857902527},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.32109999656677246},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.29739999771118164},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2793000042438507}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7576000094413757},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6601999998092651},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.6340000033378601},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.54339998960495},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4973999857902527},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3995000123977661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.387800008058548},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3790999948978424},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32670000195503235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3215999901294708},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2883000075817108},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C2987496018","wikidata":"https://www.wikidata.org/wiki/Q1860","display_name":"English language","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C74672266","wikidata":"https://www.wikidata.org/wiki/Q815859","display_name":"Language acquisition","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2540999948978424},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/itl2.70153","is_oa":false,"landing_page_url":"https://doi.org/10.1002/itl2.70153","pdf_url":null,"source":{"id":"https://openalex.org/S4210238311","display_name":"Internet Technology Letters","issn_l":"2476-1508","issn":["2476-1508"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Internet Technology Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W3205215213","https://openalex.org/W3213718839","https://openalex.org/W4220815782","https://openalex.org/W4225314877","https://openalex.org/W4313027638","https://openalex.org/W4322747041"],"related_works":[],"abstract_inverted_index":{"ABSTRACT":[0],"This":[1],"letter":[2],"presents":[3],"a":[4,12],"novel":[5],"framework":[6,90],"combining":[7],"large":[8],"language":[9,66,114],"models":[10],"with":[11],"sparse":[13],"attention":[14],"vision":[15],"transformer":[16],"(SA\u2010ViT)":[17],"to":[18,39],"classify":[19],"English":[20,36,61,80,113],"teaching":[21,81],"video":[22,53,82,101],"traffic":[23,102],"in":[24],"wireless":[25,86,117],"networks.":[26],"Our":[27],"approach":[28],"analyzes":[29],"both":[30],"visual":[31,56,111],"content":[32,42,63,123],"frames":[33,54],"and":[34,46,116],"extracted":[35],"speech":[37],"transcripts":[38],"identify":[40],"educational":[41,72,122],"types,":[43],"difficulty":[44],"levels,":[45],"priority":[47],"requirements.":[48],"The":[49,105],"proposed":[50],"model":[51],"transforms":[52],"into":[55],"patches":[57],"while":[58],"simultaneously":[59],"processing":[60],"linguistic":[62],"through":[64],"pre\u2010trained":[65],"models,":[67],"enabling":[68],"an":[69,96],"understanding":[70],"of":[71,78,110],"multimedia":[73],"traffic.":[74],"Through":[75],"extensive":[76],"evaluation":[77],"real\u2010world":[79],"datasets":[83],"transmitted":[84],"over":[85,99],"networks,":[87],"our":[88],"SA\u2010ViT":[89],"achieves":[91],"97.5%":[92],"classification":[93,103],"accuracy,":[94],"representing":[95],"11.3%":[97],"improvement":[98],"conventional":[100],"methods.":[104],"results":[106],"demonstrate":[107],"effective":[108],"integration":[109],"understanding,":[112],"comprehension,":[115],"network":[118],"optimization":[119],"for":[120],"enhanced":[121],"delivery.":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}
