Research on political text metaphor translation system based on web data mining technology
| Autor: | Shanti C. Sandaran, Wenjing Wang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Web data mining Translation system Computer science Metaphor media_common.quotation_subject General Engineering 02 engineering and technology 021001 nanoscience & nanotechnology World Wide Web Politics Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0210 nano-technology media_common |
| Zdroj: | Journal of Intelligent & Fuzzy Systems. :1-10 |
| ISSN: | 1875-8967 1064-1246 |
| DOI: | 10.3233/jifs-219150 |
| Popis: | In order to improve the translation effect of political text metaphors, based on Web data mining technology, this paper constructs a political text metaphor translation system based on Web data mining technology. Aiming at the two shortcomings of the selection of the initial center point of the K-Means algorithm and the isolated points, this paper gives a solution to the ICKM algorithm that combines the density parameter and the coordinate rotation algorithm. The algorithm uses the object with the largest density parameter as the first center point, and uses the KCR algorithm to find the next center point, which avoids the influence of isolated points on the data sample to a certain extent. The constructed political text metaphor translation system based on Web data mining technology needs to accurately translate political texts and also needs to meet the requirements of metaphor translation. Finally, this paper designs experiments to verify the system performance. The research results show that the system constructed in this paper can meet the needs of political text metaphor translation. |
| Databáze: | OpenAIRE |
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