{"id":"https://openalex.org/W4399418701","doi":"https://doi.org/10.1145/3651671.3651694","title":"Bridging Language and Culture: Applying NLP Methods for Topic Classification of Couplets using BERT","display_name":"Bridging Language and Culture: Applying NLP Methods for Topic Classification of Couplets using BERT","publication_year":2024,"publication_date":"2024-02-02","ids":{"openalex":"https://openalex.org/W4399418701","doi":"https://doi.org/10.1145/3651671.3651694"},"language":"en","primary_location":{"id":"doi:10.1145/3651671.3651694","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3651671.3651694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 16th International Conference on Machine Learning and Computing","raw_type":"proceedings-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/A5099043680","display_name":"Shayan Shariff","orcid":"https://orcid.org/0009-0009-1080-1745"},"institutions":[{"id":"https://openalex.org/I4210133438","display_name":"Habib University","ror":"https://ror.org/030p2g996","country_code":"PK","type":"education","lineage":["https://openalex.org/I4210133438"]}],"countries":["PK"],"is_corresponding":true,"raw_author_name":"Shayan Shariff","raw_affiliation_strings":["Habib University, Pakistan"],"raw_orcid":"https://orcid.org/0009-0009-1080-1745","affiliations":[{"raw_affiliation_string":"Habib University, Pakistan","institution_ids":["https://openalex.org/I4210133438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107964354","display_name":"Adam Adnan","orcid":"https://orcid.org/0009-0009-5734-1272"},"institutions":[{"id":"https://openalex.org/I4210133438","display_name":"Habib University","ror":"https://ror.org/030p2g996","country_code":"PK","type":"education","lineage":["https://openalex.org/I4210133438"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Ali Adnan","raw_affiliation_strings":["Habib University, Pakistan"],"raw_orcid":"https://orcid.org/0009-0009-5734-1272","affiliations":[{"raw_affiliation_string":"Habib University, Pakistan","institution_ids":["https://openalex.org/I4210133438"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046575650","display_name":"Muhammad Qasim Pasta","orcid":"https://orcid.org/0000-0002-9565-9881"},"institutions":[{"id":"https://openalex.org/I4210133438","display_name":"Habib University","ror":"https://ror.org/030p2g996","country_code":"PK","type":"education","lineage":["https://openalex.org/I4210133438"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Qasim Pasta","raw_affiliation_strings":["Habib University, Pakistan"],"raw_orcid":"https://orcid.org/0000-0002-9565-9881","affiliations":[{"raw_affiliation_string":"Habib University, Pakistan","institution_ids":["https://openalex.org/I4210133438"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5099043680"],"corresponding_institution_ids":["https://openalex.org/I4210133438"],"apc_list":null,"apc_paid":null,"fwci":0.6623,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73206056,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"582","last_page":"586"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9975000023841858,"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/T10028","display_name":"Topic Modeling","score":0.9975000023841858,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9952999949455261,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/urdu","display_name":"Urdu","score":0.868574857711792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7734683156013489},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7458100914955139},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7184197902679443},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.5178052186965942},{"id":"https://openalex.org/keywords/poetry","display_name":"Poetry","score":0.47759222984313965},{"id":"https://openalex.org/keywords/telugu","display_name":"Telugu","score":0.43380415439605713},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.22534465789794922}],"concepts":[{"id":"https://openalex.org/C2777350258","wikidata":"https://www.wikidata.org/wiki/Q1617","display_name":"Urdu","level":2,"score":0.868574857711792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7734683156013489},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7458100914955139},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7184197902679443},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.5178052186965942},{"id":"https://openalex.org/C164913051","wikidata":"https://www.wikidata.org/wiki/Q482","display_name":"Poetry","level":2,"score":0.47759222984313965},{"id":"https://openalex.org/C2778756302","wikidata":"https://www.wikidata.org/wiki/Q8097","display_name":"Telugu","level":2,"score":0.43380415439605713},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.22534465789794922},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3651671.3651694","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3651671.3651694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 16th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W4243903555","https://openalex.org/W4289642454","https://openalex.org/W6600424091"],"related_works":["https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W2778153218","https://openalex.org/W2748952813","https://openalex.org/W1531601525","https://openalex.org/W2261782112","https://openalex.org/W2508451165","https://openalex.org/W4225112709","https://openalex.org/W109950802","https://openalex.org/W2250347524"],"abstract_inverted_index":{"Urdu":[0,37,49,71,94,136,157,175],"poetry":[1,50],"is":[2],"a":[3,8,74,88],"captivating":[4],"art":[5],"form":[6],"with":[7],"rich":[9],"cultural":[10,79],"heritage.":[11],"This":[12],"paper":[13],"explores":[14],"the":[15,28,41,52,67,78,99,110,116,120,147,150,153,162,171],"application":[16],"of":[17,43,46,70,77,91,122,144,149,156,164],"Deep":[18],"learning":[19,107],"methods":[20],"in":[21,48,152,169],"Natural":[22],"Language":[23],"Processing":[24],"(NLP)":[25],"to":[26,63,108],"bridge":[27],"gap":[29],"between":[30],"language":[31],"and":[32,80,113,134],"culture":[33],"by":[34],"focusing":[35],"on":[36,102],"poetry.":[38,176],"We":[39,61,97,118],"investigate":[40],"task":[42],"topic":[44],"classification":[45],"couplets":[47,95],"using":[51],"powerful":[53],"BERT":[54,100,124,126,130],"(Bidirectional":[55],"Encoder":[56],"Representations":[57],"from":[58],"Transformers)":[59],"model.":[60],"aim":[62],"unlock":[64],"insights":[65],"into":[66],"thematic":[68],"content":[69],"couplets,":[72],"enabling":[73],"deeper":[75],"understanding":[76],"social":[81],"aspects":[82],"they":[83],"embody.":[84],"The":[85,138],"study":[86],"involves":[87],"comprehensive":[89],"dataset":[90],"10":[92],"thousands":[93],"collected.":[96],"fine-tune":[98],"model":[101,140],"this":[103],"dataset,":[104],"employing":[105],"transfer":[106],"capture":[109],"intricate":[111],"patterns":[112],"themes":[114],"within":[115,174],"couplets.":[117,158],"evaluate":[119],"performance":[121],"three":[123],"models,":[125],"Base":[127,131],"Multilingual":[128,132],"Uncased,":[129],"Cased,":[133],"RoBERTa":[135],"Small.":[137],"best-performing":[139],"achieves":[141],"an":[142],"accuracy":[143],"67.6%,":[145],"demonstrating":[146],"effectiveness":[148],"approach":[151],"topical":[154],"modeling":[155],"Our":[159],"findings":[160],"demonstrate":[161],"potential":[163],"NLP":[165],"techniques,":[166],"specifically":[167],"BERT,":[168],"unraveling":[170],"topics":[172],"embedded":[173]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}