{"id":"https://openalex.org/W4415072943","doi":"https://doi.org/10.1145/3767052.3767061","title":"Narrative Optimization for Chinese Enterprise English Websites via Multilingual Pretraining and Business Corpus Finetuning","display_name":"Narrative Optimization for Chinese Enterprise English Websites via Multilingual Pretraining and Business Corpus Finetuning","publication_year":2025,"publication_date":"2025-07-18","ids":{"openalex":"https://openalex.org/W4415072943","doi":"https://doi.org/10.1145/3767052.3767061"},"language":"en","primary_location":{"id":"doi:10.1145/3767052.3767061","doi":"https://doi.org/10.1145/3767052.3767061","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767052.3767061","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3767052.3767061","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Big Data, Artificial Intelligence and Digital Economy","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3767052.3767061","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Lin Pang","orcid":"https://orcid.org/0009-0007-2138-7311","observed_orcids":["https://orcid.org/0009-0007-2138-7311"]},"institutions":[{"id":"https://openalex.org/I4405271213","display_name":"Guangdong University of Science and Technology","ror":"https://ror.org/022ajrb17","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405271213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Pang","raw_affiliation_strings":["School of Foreign Languages, Guangdong University of Science and Technology, Dongguan, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0007-2138-7311","affiliations":[{"raw_affiliation_string":"School of Foreign Languages, Guangdong University of Science and Technology, Dongguan, Guangdong, China","institution_ids":["https://openalex.org/I4405271213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405271213"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26298146,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"55","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.7910000085830688,"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":0.7910000085830688,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.19349999725818634,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.0044999998062849045,"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/multilingual-pretraining","display_name":"multilingual pre-training","score":0.8980000019073486},{"id":"https://openalex.org/keywords/multilingual-transformers","display_name":"multilingual transformer models","score":0.8399999737739563},{"id":"https://openalex.org/keywords/narrative-coherence","display_name":"narrative coherence","score":0.8790000081062317},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"domain adaptation","score":0.5849999785423279},{"id":"https://openalex.org/keywords/intercultural-communication","display_name":"intercultural communication","score":0.6029999852180481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7131999731063843},{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.6639999747276306},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.44179999828338623},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4366999864578247},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.43220001459121704},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.42890000343322754},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4058000147342682},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39989998936653137},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C11693617","wikidata":"https://www.wikidata.org/wiki/Q181839","display_name":"Pragmatics","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.3668999969959259},{"id":"https://openalex.org/C134537474","wikidata":"https://www.wikidata.org/wiki/Q17144832","display_name":"Naturalness","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C2777735833","wikidata":"https://www.wikidata.org/wiki/Q5001720","display_name":"Business English","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C85890633","wikidata":"https://www.wikidata.org/wiki/Q929673","display_name":"Capability Maturity Model","level":3,"score":0.31380000710487366},{"id":"https://openalex.org/C175815440","wikidata":"https://www.wikidata.org/wiki/Q4115749","display_name":"Business communication","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C47602998","wikidata":"https://www.wikidata.org/wiki/Q2588869","display_name":"Language barrier","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C193257486","wikidata":"https://www.wikidata.org/wiki/Q3681519","display_name":"International business","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C4216890","wikidata":"https://www.wikidata.org/wiki/Q815823","display_name":"Business model","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C98147612","wikidata":"https://www.wikidata.org/wiki/Q215599","display_name":"Promotion (chess)","level":3,"score":0.2606000006198883},{"id":"https://openalex.org/C2779307921","wikidata":"https://www.wikidata.org/wiki/Q14549","display_name":"Scots","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.26010000705718994},{"id":"https://openalex.org/C532629269","wikidata":"https://www.wikidata.org/wiki/Q865083","display_name":"Corpus linguistics","level":2,"score":0.25189998745918274},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.250900000333786},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3767052.3767061","doi":"https://doi.org/10.1145/3767052.3767061","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767052.3767061","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3767052.3767061","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Big Data, Artificial Intelligence and Digital Economy","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3767052.3767061","doi":"https://doi.org/10.1145/3767052.3767061","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767052.3767061","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3767052.3767061","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Big Data, Artificial Intelligence and Digital Economy","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415072943.pdf","grobid_xml":"https://content.openalex.org/works/W4415072943.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W2955923679","https://openalex.org/W4390590848","https://openalex.org/W4403277433","https://openalex.org/W4406114214","https://openalex.org/W4407639559","https://openalex.org/W4409736197"],"related_works":[],"abstract_inverted_index":{"This":[0,152],"paper":[1],"proposes":[2],"an":[3,76],"English":[4,30,50,77,175],"text":[5],"optimization":[6,171],"model":[7,40,87,122],"that":[8,112],"integrates":[9],"multilingual":[10,45,160],"pre-training":[11],"and":[12,24,56,71,105,131,133,139,148,185],"business":[13,163],"corpus":[14,51],"fine-tuning":[15],"to":[16,62,92],"address":[17],"the":[18,29,98,113,120,143,157],"problems":[19],"of":[20,33,66,86,100,125,145,159],"low":[21],"narrative":[22,67,103,164],"quality":[23],"inconsistent":[25],"language":[26,69,101,140],"style":[27,70],"in":[28,36,123,142,162,177],"official":[31,78],"websites":[32],"Chinese":[34],"companies":[35],"international":[37],"communication.":[38],"The":[39,108],"is":[41,116],"based":[42],"on":[43],"a":[44,58,94,169],"Transformer":[46],"architecture,":[47],"combines":[48],"corporate":[49],"for":[52,173],"domain":[53],"adaptation":[54],"training,":[55],"introduces":[57],"structured":[59],"prompt":[60],"mechanism":[61],"achieve":[63],"coordinated":[64],"control":[65,88,137],"logic,":[68],"pragmatic":[72,106],"intention.":[73],"By":[74],"constructing":[75],"website":[79],"dataset":[80],"covering":[81],"multiple":[82],"industries,":[83],"five":[84],"groups":[85],"experiments":[89],"are":[90],"designed":[91],"conduct":[93],"comprehensive":[95],"evaluation":[96],"from":[97],"dimensions":[99],"quality,":[102],"coherence":[104],"consistency.":[107],"experimental":[109],"results":[110],"show":[111],"proposed":[114],"method":[115],"significantly":[117],"better":[118],"than":[119],"un-fine-tuned":[121],"terms":[124],"indicators":[126],"such":[127],"as":[128],"BLEU,":[129],"ROUGE-L,":[130],"BERTScore,":[132],"shows":[134],"stronger":[135],"structural":[136],"ability":[138],"naturalness":[141],"generation":[144,176],"brand":[146],"culture":[147],"market":[149],"communication":[150],"texts.":[151],"study":[153],"not":[154],"only":[155],"verifies":[156],"adaptability":[158],"models":[161],"scenarios,":[165],"but":[166],"also":[167],"provides":[168],"feasible":[170],"path":[172],"automatic":[174],"cross-cultural":[178],"contexts,":[179],"which":[180],"has":[181],"good":[182],"theoretical":[183],"promotion":[184],"engineering":[186],"application":[187],"value.":[188]},"counts_by_year":[],"updated_date":"2026-09-22T17:25:34.749102","created_date":"2025-10-12T00:00:00"}
