In this paper,a combined approach CAZWNLP(a combined approach of zero-watermarking and natural language processing)has been developed for the tampering detection of English text exchanged through the Internet.The thir...In this paper,a combined approach CAZWNLP(a combined approach of zero-watermarking and natural language processing)has been developed for the tampering detection of English text exchanged through the Internet.The third gram of alphanumeric of the Markov model has been used with text-watermarking technologies to improve the performance and accuracy of tampering detection issues which are limited by the existing works reviewed in the literature of this study.The third-grade level of the Markov model has been used in this method as natural language processing technology to analyze an English text and extract the textual characteristics of the given contexts.Moreover,the extracted features have been utilized as watermark information and then validated with the attacked English text to detect any suspected tampering occurred on it.The embedding mechanism of CAZWNLP method will be achieved logically without effects or modifying the original text document to embed a watermark key.CAZWNLP has been implemented using VS code IDE with PHP.The experimental and simulation results using standard datasets of varying lengths show that the proposed approach can obtain high robustness and better detection accuracy of tampering common random insertion,reorder,and deletion attacks,e.g.,Comparison results with baseline approaches also show the advantages of the proposed approach.展开更多
English text sentiment orientation analysis is a fundamental problem in the field of natural language processing.The traditional word segmentation method can produce ambiguity when dealing with English text.Therefore,...English text sentiment orientation analysis is a fundamental problem in the field of natural language processing.The traditional word segmentation method can produce ambiguity when dealing with English text.Therefore,this paper proposes a novel English text sentiment analysis based on convolutional neural network and U-network.The proposed method uses a parallel convolution layer to learn the associations and combinations between word vectors.The results are then input into the hierarchical attention network whose basic unit is U-network to determine the affective tendency.The experimental results show that the accuracy of bias classification on the English review dataset reaches 93.45%.Compared with many existing sentiment analysis models,it has more accuracy.展开更多
Guangxi tourism texts are a kind of tool to show China's image.However,there are still lots of problems despite certain achievements in recent years in Chinese-to-English(C-E) translation of tourism texts.So,how t...Guangxi tourism texts are a kind of tool to show China's image.However,there are still lots of problems despite certain achievements in recent years in Chinese-to-English(C-E) translation of tourism texts.So,how to improve the quality of tourism materials is of great significance practically.The aim is to adopt the"Creation"Thought of Guo Moruo that emphasizes creation,charming translation,having empathy with the source language and experience,aiming at discovering proper and feasible translation standards and strategies and making it better serve for the tourism development between Guangxi and ASEAN countries.展开更多
This paper is designed to explore whether the theory of text linguistics,especially the knowledge of cohesion,coherence and cohesive devices could be applied in college English writing teaching to help improve student...This paper is designed to explore whether the theory of text linguistics,especially the knowledge of cohesion,coherence and cohesive devices could be applied in college English writing teaching to help improve students’writing abilities.Besides,the author puts forward some suggestions for both English teachers and learners.展开更多
The author compares Chinese and western language features in tourist texts, shares four strategies in translating Chinese tourist texts,and calls on building a corpus for Chinese-English translation of tourist texts.
为实现英文文本标题的自动化生成,研究一套基于长短期记忆网络的句子级LSTM编码策略,并在标题生成模型中引入注意力机制来获取英文文本的上下文向量,保留文本中的重要信息。在此基础上,通过负对数似然函数来对模型加以训练。最后通过Byt...为实现英文文本标题的自动化生成,研究一套基于长短期记忆网络的句子级LSTM编码策略,并在标题生成模型中引入注意力机制来获取英文文本的上下文向量,保留文本中的重要信息。在此基础上,通过负对数似然函数来对模型加以训练。最后通过Byte Cup 2018数据集对本文提出的英语标题自动生成算法进行实验,并通过过ROUGE-N指标对标题生成质量加以评价。实验研究发现,所提出的句子级LSTM编码方案在英文文本标题生成准确性方面相比于其他常规摘要生成模型来说具有显著优势。展开更多
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under grant number(R.G.P.2/55/40/2019)Received by Fahd N.Al-Wesabi.www.kku.edu.sa。
文摘In this paper,a combined approach CAZWNLP(a combined approach of zero-watermarking and natural language processing)has been developed for the tampering detection of English text exchanged through the Internet.The third gram of alphanumeric of the Markov model has been used with text-watermarking technologies to improve the performance and accuracy of tampering detection issues which are limited by the existing works reviewed in the literature of this study.The third-grade level of the Markov model has been used in this method as natural language processing technology to analyze an English text and extract the textual characteristics of the given contexts.Moreover,the extracted features have been utilized as watermark information and then validated with the attacked English text to detect any suspected tampering occurred on it.The embedding mechanism of CAZWNLP method will be achieved logically without effects or modifying the original text document to embed a watermark key.CAZWNLP has been implemented using VS code IDE with PHP.The experimental and simulation results using standard datasets of varying lengths show that the proposed approach can obtain high robustness and better detection accuracy of tampering common random insertion,reorder,and deletion attacks,e.g.,Comparison results with baseline approaches also show the advantages of the proposed approach.
文摘English text sentiment orientation analysis is a fundamental problem in the field of natural language processing.The traditional word segmentation method can produce ambiguity when dealing with English text.Therefore,this paper proposes a novel English text sentiment analysis based on convolutional neural network and U-network.The proposed method uses a parallel convolution layer to learn the associations and combinations between word vectors.The results are then input into the hierarchical attention network whose basic unit is U-network to determine the affective tendency.The experimental results show that the accuracy of bias classification on the English review dataset reaches 93.45%.Compared with many existing sentiment analysis models,it has more accuracy.
文摘Guangxi tourism texts are a kind of tool to show China's image.However,there are still lots of problems despite certain achievements in recent years in Chinese-to-English(C-E) translation of tourism texts.So,how to improve the quality of tourism materials is of great significance practically.The aim is to adopt the"Creation"Thought of Guo Moruo that emphasizes creation,charming translation,having empathy with the source language and experience,aiming at discovering proper and feasible translation standards and strategies and making it better serve for the tourism development between Guangxi and ASEAN countries.
文摘This paper is designed to explore whether the theory of text linguistics,especially the knowledge of cohesion,coherence and cohesive devices could be applied in college English writing teaching to help improve students’writing abilities.Besides,the author puts forward some suggestions for both English teachers and learners.
文摘The author compares Chinese and western language features in tourist texts, shares four strategies in translating Chinese tourist texts,and calls on building a corpus for Chinese-English translation of tourist texts.
文摘为实现英文文本标题的自动化生成,研究一套基于长短期记忆网络的句子级LSTM编码策略,并在标题生成模型中引入注意力机制来获取英文文本的上下文向量,保留文本中的重要信息。在此基础上,通过负对数似然函数来对模型加以训练。最后通过Byte Cup 2018数据集对本文提出的英语标题自动生成算法进行实验,并通过过ROUGE-N指标对标题生成质量加以评价。实验研究发现,所提出的句子级LSTM编码方案在英文文本标题生成准确性方面相比于其他常规摘要生成模型来说具有显著优势。
