Semantic Analysis of Literary Vocabulary Based on Microsystem and Computer Aided Deep Research

Abstract

It has great advantages in data processing. Embedded microsystems are widely used in IoT devices because of their specific functions and hard decoding technology. This article adds a literary vocabulary semantic analysis model to the embedded microsystem to reduce power consumption and improve the accuracy and speed of the system. The main purpose of this paper is to improve the accuracy and speed of semantic analysis of literary vocabulary based on the embedded microsystem, combined with the design idea of Robot Process Automation (RPA) and adding CNN logic algorithm. In this paper, RPA Adam model is proposed. The RPA Adam model indicates that the vector in the vector contains not only the characteristics of its own node but also the characteristics of neighboring nodes. It is applied to graph convolution network of isomorphic network analysis and analyzes the types of devices that can be carried by embedded chips, and displays them with graphics. Through the results, we find that the error rate of the RPA Adam model is the same at different compression rates. Due to the different correlations between knowledge entities in different data sets, specifically, high frequency can maintain a low bit error rate of 10.79% when the compression rate is 4.85%, but when the compression rate of high frequency is only 60.32%, the error rate is as high as 11.26%, while the compression rate of low frequency is 23.51% when the error rate is 9.65%.

Imagery Recognition and Semantic Analysis Techniques in Chinese Literary Texts

“…Literature [11] designed a semantic analysis framework to recognize and guide students' emotions in using the MOOC platform to provide guidance and recommendations adapted to students' emotions and actual needs to enhance their learning outcomes. Literature [12] attempted to introduce a lexical semantic analysis framework for literary utterances into embedded microsystems, which effectively reduces the accuracy rate and efficiency of the system in the vocabulary recognition processing of literary utterances.…”

Research on English Vocabulary and Speech Corpus Recognition Based on Deep Learning

“…Some institutions in China, such as PLASER at Hong Kong University of Science and Technology, Department of Electronic Engineering at Tsinghua University, Department of Computer Science of Harbin Institute of Technology, and the Department of Computer Science of Harbin Institute of Technology, have also made some significant progress in these researches. However, most researches in China were to assist the learning of Chinese pronunciation [9].…”