基于上下文同义词替换的句法分析方法

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
A. Barmawi, Ali Muhammad
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引用次数: 3

摘要

转述生成是自然语言处理和生成的重要组成部分。有几种使用转述的应用,例如语言隐写术、推荐系统、机器翻译等。转述句子的一种方法是使用同义词替换,例如Gadag等人提出的基于NGM的转述方法。这种方法的缺点是,由于转述过程完全基于n-gram,因此经常出现歧义。这会对转述句子的自然性产生负面影响。为了克服这一问题,提出了一种上下文同义词替换方法,旨在提高转述句的自然度。使用所提出的方法,转述过程不仅基于n-gram,而且基于句子的上下文,从而提高了自然度。根据实验结果,使用所提出的方法生成的句子比使用原始方法生成的语句具有更高的自然度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Paraphrasing Method Based on Contextual Synonym Substitution
Generating paraphrases is an important component of natural language processing and generation. There are sev­eral applications that use paraphrasing, for example linguistic steganography, recommender systems, machine translation, etc. One method for paraphrasing sentences is by using synonym substitution, such as the NGM-based paraphrasing method proposed by Gadag et al. The weakness of this method is that ambiguous meanings frequently occur because the paraphrasing process is based solely on n-gram. This negatively affects the naturalness of the paraphrased sentences. For overcoming this problem, a contextual synonym substitution method is proposed, which aims to increase the naturalness of the paraphrased sentences. Using the proposed method, the paraphrasing process is not only based on n-gram but also on the context of the sentence such that the naturalness is increased. Based on the experimental result, the sentences generated using the proposed method had higher naturalness than the sentences generated using the original method.
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来源期刊
Journal of ICT Research and Applications
Journal of ICT Research and Applications COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
1.60
自引率
0.00%
发文量
13
审稿时长
24 weeks
期刊介绍: Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management. Authors are invited to submit articles that have not been published previously and are not under consideration elsewhere.
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