Journal of Applied Science and Engineering

Published by Tamkang University Press

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Informationization Design of College English Corpus Using Deep Learning Algorithms

 2026

 Volume 32

Cheng Lin and Ruixue Li

School of Foreign Languages, Jiujing University, Jiujiang Jiangxi, 332005, China

Received: February 21, 2026
Accepted: March 27, 2026
Publication Date: May 4, 2026

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This study proposes the ISSO-SNN model for semantic readability assessment in a college English corpus, addressing limitations of traditional methods. Using NLP preprocessing and TF-IDF features, the model leverages a Siamese network optimized with ISSO for improved prediction. The study proposes an Intelligent Shuffled Shepherd Optimized Siamese Neural Network (ISSO-SNN) model for semantic readability assessment in a college English corpus. Implemented in Python 3.11, it achieved high performance (accuracy 0.98, precision 0.97, recall 0.97 , F1 0.98 ), supporting effective and personalized English learning.

Keywords: Natural Language Processing (NLP); Intelligent Shuffled Shepherd optimized Siamese Neural Network (ISSO-SNN); deep learning (DL); English Corpus

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