@article {746,
	title = {Improvement of English-Chinese Translation Method by Feature Reduction and Rule Optimization Based on Rough Set Theory-},
	journal = {Journal of Digital Information Management},
	volume = {21},
	year = {2023},
	month = {09-2023},
	pages = {83-87},
	type = {Research},
	chapter = {83},
	abstract = {<p>The traditional machine translation algorithm faces low efficiency and low accuracy due to complex grammar and multiple rules of English noun phrases. A kind of noun phrase identification method based on a rough set was proposed to improve the accuracy of English noun phrases. The rough set method regarded the identification of English noun phrases as a decision problem. We used rough set theory to reduce features, optimize rules for English noun phrases, and finally identify them. Then, a simulation experiment was carried out on an English noun phrase sample on the Wall Street Journal (WSJ) using rough set theory. The stimulation demonstrated that the accuracy of the noun phrase improved by the rough set was higher than another translation method; therefore, it is an effective machine identification method for English noun phrases, providing a basis for practical design.</p>
},
	doi = {https://doi.org/10.6025/jdim/2023/21/3/83-87},
	url = {http://www.dline.info/download.php?sn=3837},
	author = {Hongxia Wei}
}
