Ji Yu Shen Ceng Lei Shen Jing Wang Lu Ji Biao Shi Xue Xi Ji Shu Zhi Wen Jian Ke Du Xing Fen Lei (Classification of Text Readability Based on Deep Neural Network and Representation Learning Techniques)[In Chinese]
The development of the internet has facilitated the flow of information. However, this explosive growth of information has led to fundamental importance being overlooked: Reading material can be understood. Research on readability formulas aims to predict, to a reasonable extent, the degree to which a text can be understood. It does so mainly by analyzing and translating the information within a text into readability features, which are used to train a readability model, in order to automatically predict the readability of a given text. In recent years, the development of deep neural networks, applied to speech recognition, image processing and natural language processing has improved significantly on the performance. Therefore, this paper proposes a readability model built with deep neural network and word vector representation, and which is capable of analyzing cross domain texts, in accordance with the diverse topics of text contents. The authors aim to make the readability model capable of analyzing text readability with more accurate, as well as possess domain generalization capacity. Guan Jian Ci :Ke Du Xing ,Ci Xiang Liang ,Fen Lei ,Shen Ceng Lei Shen Jing Wang Lu ,Zhi Xiang Liang Ji
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