基于智能优化算法的文本比对分析与评价

Zixian Fang, Jiayi Wang, Fenglan Luo
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引用次数: 0

摘要

文本转录是汉语信息处理的关键。文字抄写自古以来就有,但无论是古代的人工抄写,还是现代利用通信和存储设备抄写,一条信息经过多次转发和抄写,难免会出现随机错误。本文针对文本转录的特点,研究了如何衡量文本不同版本之间的差异大小,如何估计两个文本之间的传输次数,以及如何设计一种有效快速的算法来计算文本转录研究中的前两类问题。本文提出文本相似度的概念,构建文本的TF-IDF相似度评价模型、基于高斯过程的文本传输评价模型(即GFCT模型)和基于免疫跳蛙算法的模型,对文本的比较处理进行分析,从而实现准确有效的信息处理,以期为文本数据处理提供一种新的方法,提高文本数据处理的准确性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis and Evaluation of Text Comparison Based on Intelligent Optimization Algorithm
Text transcription is crucial in Chinese information processing. Text transcription has always existed since ancient times, but no matter whether it is manual transcription in ancient times or modern transcription using communication and storage devices, random errors cannot be avoided when a message has been forwarded and transcribed many times. In this paper, we study how to measure the size of differences between different versions of texts, how to estimate the number of transmissions experienced between two texts, and how to design an effective and fast algorithm for the calculation of the first two types of problems in the study of text transcription, with respect to the characteristics of text transcription. This paper proposes the concept of text similarity, constructs the TF-IDF similarity evaluation model of text, the text transmission evaluation model based on Gaussian process (i.e., GFCT Model), and the model based on the immune frog jumping algorithm to analyze the comparative processing of text, so as to achieve accurate and effective information processing, with a view to providing a new method for text data processing, and improving the accuracy and effectiveness of text data processing.
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