Affiliation:
1. School of Foreign Languages, Shaoxing University, Shaoxing 312000, China
Abstract
To study the influence of conventional literature on foreign literature driven by big data, this essay begins with surveys and interviews. Chinese big data-driven corpora are distinct from other Chinese corpora, as is widely known. Its main objective is to categorize professional corpora that are unknown and fall within the category of professional corpora. In order to provide a straightforward and useful domain partitioning model for corpus texts, this research makes use of text clustering and big data-driven methodologies. We can easily determine the domain of the aligned text, making it easier to do machine translation research in the future. The research findings demonstrate that the accuracy rate of the approach suggested in this article is essentially above 89.79%, demonstrating the viability of the way of automatically building a corpus suggested in this paper in the experiment.
Funder
Zhejiang Federation of Humanities and Social Sciences Planning Project
Subject
Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health
Cited by
1 articles.
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