Research on the Public Perception of Yangzhou Historical and Cultural Districts Based on Network Review Text Analysis

The historical and cultural districts of a city serve as important cultural heritage and tourism resources.This paper focused on four such districts in Yangzhou and performed semantic analysis on online public comments using ROST CM6 software.According to the high frequency words,attention preference of district site elements,activities and feelings in Yangzhou historical and cultural districts were analyzed.Through the analysis of semantic network and public emotional tendency,the relationship between the protection and utilization of Yangzhou historical and cultural districts and the perception and demand of users were discussed,and some suggestions for the protection,utilization and renewal of historical and cultural districts were put forward.

Priorities for Social and Humanities Projects Based on Text Analysis

Purpose:Changes in the world show that the role,importance,and coherence of SSH(social sciences and the humanities)will increase significantly in the coming years.This paper aims to monitor and analyze the evolution(or overlapping)of the SSH thematic pattern through three funding instruments since 2007.Design/methodology/approach:The goal of the paper is to check to what extent the EU Framework Program(FP)affects/does not affect research on national level,and to highlight hot topics from a given period with the help of text analysis.Funded project titles and abstracts derived from the EU FP,Slovenian,and Estonian RIS were used.The final analysis and comparisons between different datasets were made based on the 200 most frequent words.After removing punctuation marks,numeric values,articles,prepositions,conjunctions,and auxiliary verbs,4,854 unique words in ETIS,4,421 unique words in the Slovenian Research Information System(SICRIS),and 3,950 unique words in FP were identified.Findings:Across all funding instruments,about a quarter of the top words constitute half of the word occurrences.The text analysis results show that in the majority of cases words do not overlap between FP and nationally funded projects.In some cases,it may be due to using different vocabulary.There is more overlapping between words in the case of Slovenia(SL)and Estonia(EE)and less in the case of Estonia and EU Framework Programmes(FP).At the same time,overlapping words indicate a wider reach(culture,education,social,history,human,innovation,etc.).In nationally funded projects(bottom-up),it was relatively difficult to observe the change in thematic trends over time.More specific results emerged from the comparison of the different programs throughout FP(top-down).Research limitations:Only projects with English titles and abstracts were analyzed.Practical implications:The specifics of SSH have to take into account—the one-to-one meaning of terms/words is not as important as,for example,in the exact sciences.Thus,even in co-word analysis,the final content may go unnoticed.Originality/value:This was the first attempt to monitor the trends of SSH projects using text analysis.The text analysis of the SSH projects of the two new EU Member States used in the study showed that SSH’s thematic coverage is not much affected by the EU Framework Program.Whether this result is field-specific or country-specific should be shown in the following study,which targets SSH projects in the so-called old Member States.

Text Analysis-Based Watermarking Approach for Tampering Detection of English Text

Due to the rapid increase in the exchange of text information via internet networks,the security and the reliability of digital content have become a major research issue.The main challenges faced by researchers are authentication,integrity verication,and tampering detection of the digital contents.In this paper,text zero-watermarking and text feature-based approach is proposed to improve the tampering detection accuracy of English text contents.The proposed approach embeds and detects the watermark logically without altering the original English text document.Based on hidden Markov model(HMM),the fourth level order of the word mechanism is used to analyze the contents of the given English text to nd the interrelationship between the contexts.The extracted features are used as watermark information and integrated with digital zero-watermarking techniques.To detect eventual tampering,the proposed approach has been implemented and validated with attacked English text.Experiments were performed using four standard datasets of varying lengths under multiple random locations of insertion,reorder,and deletion attacks.The experimental and simulation results prove the tampering detection accuracy of our method against all kinds of tampering attacks.Comparison results show that our proposed approach outperforms all the other baseline approaches in terms of tampering detection accuracy.

The Thematic Progression Patterns and Text Analysis of Necklace

This paper is an attempt to discuss the relationship between genre and the thematic progression. Through qualitative analysis of the short story Necklace of Maupassant, it is found that narrative texts always use the linear theme pattern and the constant theme pattern, and sometimes the derived theme pattern and other patterns are also used to facilitate the text coherence and the plot development. Thematic progression in various fields has been studied extensively, but the analysis aims to short story is less than text coherence and other aspects. And there are some implications to teaching, writing, reading, and translation.

On the Greatness of The Great Gatsby——About the Text Analysis of The Great Gatsby

The Great Gatsby is universally recognized as one of the masterpieces in the world literature. This thesis adopts the methods of comparison, contrast, and quotation to explore why Great Gatsby is great. This thesis analyzes the text from the three aspects:the greatness in Gatsby's economic success, the greatness in Gatsby's perseverance of love, the greatness of Gatsby's personality. In this way, the readers can understand the great Gatsby's greatness.

A quantum‐like approach for text generation from knowledge graphs

Recent text generation methods frequently learn node representations from graph‐based data via global or local aggregation,such as knowledge graphs.Since all nodes are connected directly,node global representation encoding enables direct communication between two distant nodes while disregarding graph topology.Node local representation encoding,which captures the graph structure,considers the connections between nearby nodes but misses out onlong‐range relations.A quantum‐like approach to learning bettercontextualised node embeddings is proposed using a fusion model that combines both encoding strategies.Our methods significantly improve on two graph‐to‐text datasets compared to state‐of‐the‐art models in various experiments.

Automatic Persian Text Summarization Using Linguistic Features from Text Structure Analysis

With the remarkable growth of textual data sources in recent years,easy,fast,and accurate text processing has become a challenge with significant payoffs.Automatic text summarization is the process of compressing text documents into shorter summaries for easier review of its core contents,which must be done without losing important features and information.This paper introduces a new hybrid method for extractive text summarization with feature selection based on text structure.The major advantage of the proposed summarization method over previous systems is the modeling of text structure and relationship between entities in the input text,which improves the sentence feature selection process and leads to the generation of unambiguous,concise,consistent,and coherent summaries.The paper also presents the results of the evaluation of the proposed method based on precision and recall criteria.It is shown that the method produces summaries consisting of chains of sentences with the aforementioned characteristics from the original text.

A Hybrid Intelligent Approach for Content Authentication and Tampering Detection of Arabic Text Transmitted via Internet

In this paper,a hybrid intelligent text zero-watermarking approach has been proposed by integrating text zero-watermarking and hidden Markov model as natural language processing techniques for the content authentication and tampering detection of Arabic text contents.The proposed approach known as Second order of Alphanumeric Mechanism of Markov model and Zero-Watermarking Approach(SAMMZWA).Second level order of alphanumeric mechanism based on hidden Markov model is integrated with text zero-watermarking techniques to improve the overall performance and tampering detection accuracy of the proposed approach.The SAMMZWA approach embeds and detects the watermark logically without altering the original text document.The extracted features are used as a watermark information and integrated with digital zero-watermarking techniques.To detect eventual tampering,SAMMZWA has been implemented and validated with attacked Arabic text.Experiments were performed on four datasets of varying lengths under multiple random locations of insertion,reorder and deletion attacks.The experimental results show that our method is more sensitive for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.

An Optimized English Text Watermarking Method Based on Natural Language Processing Techniques

In this paper,the text analysis-based approach RTADZWA(Reliable Text Analysis and Digital Zero-Watermarking Approach)has been proposed for transferring and receiving authentic English text via the internet.Second level order of alphanumeric mechanism of hidden Markov model has been used in RTADZWA approach as a natural language processing to analyze the English text and extracts the features of the interrelationship between contexts of the text and utilizes the extracted features as watermark information and then validates it later with attacked English text to detect any tampering occurred on it.Text analysis and text zero-watermarking techniques have been integrated by RTADZWA approach to improving the performance,accuracy,capacity,and robustness issues of the previous literature proposed by the researchers.The RTADZWA approach embeds and detects the watermark logically without altering the original text document to embed a watermark.RTADZWA has been implemented using PHP with VS code IDE.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.

Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text

Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication technology.In this paper,a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking(SFASCDW)is proposed for content authentication and tampering detection of English text.A first-level order of alphanumeric mechanism,based on hidden Markov model,is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed approach.The researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English text.Moreover,he extracts the features of the interrelationship among the contexts of the text,utilizes the extracted features as watermark information,and validates it later with the studied English text to detect any tampering.SFASCDW has been implemented using PHP with VS code IDE.The robustness,effectiveness,and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks,namely insertion,reorder,and deletion.The SFASCDW was found to be effective and could be applicable in detecting any possible tampering.

Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack

In this article,a high-sensitive approach for detecting tampering attacks on transmitted Arabic-text over the Internet(HFDATAI)is proposed by integrating digital watermarking and hidden Markov model as a strategy for soft computing.The HFDATAI solution technically integrates and senses the watermark without modifying the original text.The alphanumeric mechanism order in the first stage focused on the Markov model key secret is incorporated into an automated,null-watermarking approach to enhance the proposed approach’s efficiency,accuracy,and intensity.The first-level order and alphanumeric Markov model technique have been used as a strategy for soft computing to analyze the text of the Arabic language.In addition,the features of the interrelationship among text contexts and characteristics of watermark information extraction that is used later validated for detecting any tampering of the Arabic-text attacked.The HFDATAI strategy was introduced based on PHP with included IDE of VS code.Experiments of four separate duration datasets in random sites illustrate the fragility,efficacy,and applicability of HFDATAI by using the three common tampering attacks i.e.,insertion,reorder,and deletion.The HFDATAI was found to be effective,applicable,and very sensitive for detecting any possible tampering on Arabic text.

An Optimal Text Watermarking Method for Sensitive Detecting of Illegal Tampering Attacks

Due to the rapid increase in the exchange of text information via internet networks,the security and authenticity of digital content have become a major research issue.The main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital text.In this paper,an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on theArabic text transmitted online via an Internet network.Towards this purpose,the accuracy of tampering detection and watermark robustness has been improved of the proposed method as compared with the existing approaches.In the proposed method,both embedding and extracting of the watermark are logically implemented,which causes no change in the digital text.This is achieved by using the third level and alphanumeric strategy of the Markov model as a text analysis technique for analyzing the Arabic contents to obtain its features which are considered as the digital watermark.This digital watermark will be used later to detecting any tampering of illegal attack on the received Arabic text.An extensive set of experiments using four data sets of varying lengths proves the effectiveness of our approach in terms of detection accuracy,robustness,and effectiveness under multiple random locations of the common tampering attacks.

A Reliable NLP Scheme for English Text Watermarking Based on Contents Interrelationship

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.

Analysis of Multiple Dimensions of“Another”in In Another Country

Hemingway’s In Another Country expresses rich ideological connotation with extremely concise language,and reveals the cruelty of war and the huge trauma caused by war to human body and mind.This paper explores the multiple meanings of“an⁃other”in this short story by analyzing the background,environment,character identity,social relationship and personal concept.

A Study on Brand Personality of Coastal Tourism Destinations:Text Mining Approach

As the core element of the brand,brand personality is closely related to the personality of tourists.Unique and distinctive brand personality has become an important means for tourism destinations to enhance their core competitiveness.Through text analysis,the content of the online review content of three coastal tourist destinations in Yalong Bay,Silver Beach,and Gulangyu Islet were analyzed.The brand personality of coastal tourist destinations was identified from the perspective of tourist perception,and the selected 3 coastal tourist destinations were identified by correspondence analysis.Comparative analysis on a case-by-case basis.The research results show that the brand personality of coastal tourism destinations perceived by tourists is mainly concentrated in the two dimensions of“elegance”and“benevolence”,but different coastal tourism destinations have their own distinct and unique brand personalities.On this basis,directional suggestions for the development of brand personality in coastal tourism destinations are given.

Analysis of the trend of global power sources based on comment emotion mining

In recent years,renewable energy technologies have been developed vigorously,and related supporting policies have been issued.The developmental trend of different energy sources directly affects the future developmental pattern of the energy and power industry.Energy trend research can be quantified through data statistics and model calculations;however,parameter settings and optimization are difficult,and the analysis results sometimes do not reflect objective reality.This paper proposes an energy and power information analysis method based on emotion mining.This method collects energy commentary news and literature reports from many authoritative media around the world and builds a convolutional neural network model and a text analysis model for topic classification and positive/negative emotion evaluation,which helps obtain text evaluation matrixes for all collected texts.Finally,a long-short-term memory model algorithm is employed to predict the future development prospects and market trends for various types of energy based on the analyzed emotions in different time spans.Experimental results indicate that energy trend analysis based on this method is consistent with the real scenario,has good applicability,and can provide a useful reference for the development of energy and power resources and of other industry areas as well.

普惠型商业医疗保险特定高额药品保障研究

目的研究我国普惠型商业医疗保险目前特定高额药品(以下简称“特药”)保障的范围及水平,为进一步完善普惠型商业医疗保险的保障水平提供参考。方法通过官方公众号、投保小程序收集2022年普惠型商业医疗保险的保障政策,采用政策文本分析法提取和分析参保条件、筹资标准、特药的类别及保障水平等内容。结果2022年普惠型商业医疗保险所包含特药数量的均数为28种,以肿瘤药为主。54.62%的商业医疗保险方案特药起付线设定为0,报销比例的均数为74%、中位数为80%。70.54%的商业医疗保险方案封顶线在100万元及以下。58.04%的商业医疗保险方案保障既往症人群的特药费用,但保障水平在不同程度上有所降低。结论我国普惠型商业医疗保险的特药保障有助于减轻患者的经济负担,满足患者多元化用药需求,但对既往症人群的保障水平较为有限。建议进一步优化特药保障责任,明确特药目录的遴选规则。

The evolution of central environmental protection inspection policy attention in China: An investigation based on inspection reports

The central environmental protection inspection (CEPI) system in China is a significant institutional innova‐tion in national environmental governance. The CEPI applies a joint supervision strategy to address salient en‐vironmental issues and strictly enforce the environmental responsibilities of local governments. This study col‐lects and organizes CEPI inspection reports covering three stages that encompass the first round, the “look back”, and the second round, applying text analysis to obtain sample data and conduct statistical quantifica‐tion of word frequency in inspection reports and identify notable changes. The study explores the allocation of CEPI attention between policy objectives and the intensity of policy instruments. We determine that in con‐junction with public opinion feedback, the CEPI conducts targeted inspections and focuses more on pollutant governance, which has high severity and can be addressed quickly. The CEPI fills the gap of normalized gover‐nance with a campaign-style governance approach. Regarding the intensity of policy measures, the CEPI pri‐marily uses economic incentive policy instruments, supplemented by command-and-control and public guid‐ance approaches, advancing the sustainability of regulatory effectiveness through economic, social, and politi‐cal activities. This study extends knowledge in the field of CEPI policy priorities and implementation, expand‐ing the literature related to outcomes of environmental policy in developing countries.

Numerical‐discrete‐scheme‐incorporated recurrent neural network for tasks in natural language processing

A variety of neural networks have been presented to deal with issues in deep learning in the last decades.Despite the prominent success achieved by the neural network,it still lacks theoretical guidance to design an efficient neural network model,and verifying the performance of a model needs excessive resources.Previous research studies have demonstrated that many existing models can be regarded as different numerical discretizations of differential equations.This connection sheds light on designing an effective recurrent neural network(RNN)by resorting to numerical analysis.Simple RNN is regarded as a discretisation of the forward Euler scheme.Considering the limited solution accuracy of the forward Euler methods,a Taylor‐type discrete scheme is presented with lower truncation error and a Taylor‐type RNN(T‐RNN)is designed with its guidance.Extensive experiments are conducted to evaluate its performance on statistical language models and emotion analysis tasks.The noticeable gains obtained by T‐RNN present its superiority and the feasibility of designing the neural network model using numerical methods.

Inheritance of Red Culture and Perception of Tourism Development in Yimeng under the Background of Cultural and Tourism Integration

Developing red tourism is an important way to carry forward revolutionary culture and practice socialist core values.In this paper,effective comments on tourism websites such as“Ctrip”and“Tongcheng Travel”were selected as data sources,and with the help of network text analysis,the image perception and emotion of tourists in Linyi red tourism were analyzed.Besides,new ways to develop and utilize red tourism in Linyi City were put forward,such as innovating red tourism experiential products,promoting industrial linkage and common development,improving red tourism service facilities,and focusing on network marketing models,so as to reshape the red tourism value chain and enhance the comprehensive social effect.