A study of paraphrase meta-language in linguistic domains in the age of artificial intelligence
This study delves into paraphrase meta-language for linguistic domains in the age of artificial intelligence. The study includes text preprocessing, text representation based on vector space modeling, statistical disambiguation, feature selection, and LDA topic modeling application. The research res...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
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| Online Access: | https://doi.org/10.2478/amns-2024-0610 |
| _version_ | 1797279118933360640 |
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| author | Peng Tongtong |
| author_facet | Peng Tongtong |
| author_sort | Peng Tongtong |
| collection | DOAJ |
| description | This study delves into paraphrase meta-language for linguistic domains in the age of artificial intelligence. The study includes text preprocessing, text representation based on vector space modeling, statistical disambiguation, feature selection, and LDA topic modeling application. The research results show that these methods can effectively extract and understand paraphrased meta-language. The thematic distribution and dynamic changes of paraphrased meta-language are revealed by LDA modeling analysis in 4623552 Twitter data and 532565 linguistic documents. In addition, this study empirically analyzes paraphrase meta-language based on lexical understanding and finds that the average correctness of the annotators meets the expected range in all types of polysemous words. In the era of artificial intelligence, the study of paraphrase meta-language can bring new insights to linguistics, especially showing its value in understanding and processing large-scale linguistic data. |
| first_indexed | 2024-03-07T16:19:39Z |
| format | Article |
| id | doaj.art-549940dba1e94875a4a3b17709c81ae1 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-07T16:19:39Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-549940dba1e94875a4a3b17709c81ae12024-03-04T07:30:43ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns-2024-0610A study of paraphrase meta-language in linguistic domains in the age of artificial intelligencePeng Tongtong01Nanjing Normal University, International College for Chinese Studies, Nanjing, Jiangsu, 210097, China.This study delves into paraphrase meta-language for linguistic domains in the age of artificial intelligence. The study includes text preprocessing, text representation based on vector space modeling, statistical disambiguation, feature selection, and LDA topic modeling application. The research results show that these methods can effectively extract and understand paraphrased meta-language. The thematic distribution and dynamic changes of paraphrased meta-language are revealed by LDA modeling analysis in 4623552 Twitter data and 532565 linguistic documents. In addition, this study empirically analyzes paraphrase meta-language based on lexical understanding and finds that the average correctness of the annotators meets the expected range in all types of polysemous words. In the era of artificial intelligence, the study of paraphrase meta-language can bring new insights to linguistics, especially showing its value in understanding and processing large-scale linguistic data.https://doi.org/10.2478/amns-2024-0610ldavector space modelingtext featuresstatistical disambiguationparaphrased meta-language62n01 |
| spellingShingle | Peng Tongtong A study of paraphrase meta-language in linguistic domains in the age of artificial intelligence Applied Mathematics and Nonlinear Sciences lda vector space modeling text features statistical disambiguation paraphrased meta-language 62n01 |
| title | A study of paraphrase meta-language in linguistic domains in the age of artificial intelligence |
| title_full | A study of paraphrase meta-language in linguistic domains in the age of artificial intelligence |
| title_fullStr | A study of paraphrase meta-language in linguistic domains in the age of artificial intelligence |
| title_full_unstemmed | A study of paraphrase meta-language in linguistic domains in the age of artificial intelligence |
| title_short | A study of paraphrase meta-language in linguistic domains in the age of artificial intelligence |
| title_sort | study of paraphrase meta language in linguistic domains in the age of artificial intelligence |
| topic | lda vector space modeling text features statistical disambiguation paraphrased meta-language 62n01 |
| url | https://doi.org/10.2478/amns-2024-0610 |
| work_keys_str_mv | AT pengtongtong astudyofparaphrasemetalanguageinlinguisticdomainsintheageofartificialintelligence AT pengtongtong studyofparaphrasemetalanguageinlinguisticdomainsintheageofartificialintelligence |