Assessing trends in wildland-urban interface fire research through text mining: a comprehensive analysis of published literature

Research on fires at the wildland-urban inter-face(WUI)has generated significant insights and advance-ments across various fields of study.Environmental,agri-culture,and social sciences have played prominent roles in understanding the impacts of fires in the environment,in protecting communities,and addressing management challenges.This study aimed to create a database using a text mining technique for global researchers interested in WUI-projects and highlighting the interest of countries in this field.Author’s-Keywords analysis emphasized the dominance of fire science-related terms,especially related to WUI,and identified keyword clusters related to the WUI fire-risk-assessment-system-“exposure”,“danger”,and“vulnerability”within wildfire research.Trends over the past decade showcase shifting research interests with a growing focus on WUI fires,while regional variations highlighted that the“exposure”keyword cluster received greater atten-tion in the southern Europe and South America.However,vulnerability keywords have relatively a lower representation across all regions.The analysis underscores the interdisci-plinary nature of WUI research and emphasizes the need for targeted approaches to address the unique challenges of the wildland-urban interface.Overall,this study provides valu-able insights for researchers and serves as a foundation for further collaboration in this field through the understanding of the trends over recent years and in different regions.

Text type, language function and translation strategy of film lines

For different texts, different translation strategies should be adopted. This paper makes a case study on lines from Disney animation picture Mulan in the light of functional concept of translation. And it draws a conclusion that in the process of film translation, the translator is allowed to make some adaptations to make the translated version more appropriate in the original context, and that the translator is supposed to have both ＂semantic awareness＂ and ＂functional awareness＂, to achieve the equivalence between the SL text and TL text functionally.

Visualization of Special Features in “The Tale of Genji” by Text Mining and Correspondence Analysis with Clustering

In this paper, visualization of special features in “The Tale of Genji”, which is a typical Japanese classical literature, is studied by text mining the auxiliary verbs and examining the similarity in the sentence style by the correspondence analysis with clustering. The result shows that the text mining error in the number of auxiliary verbs can be as small as 15%. The extracted feature in this study supports the multiple authors of “The Tale of Genji”, which agrees well with the result by Murakami and Imanishi [1]. It is also found that extracted features are robust to the text mining error, which suggests that the classification error is less affected by the text mining error and the possible use of this technique for further statistical study in classical literatures.

Fuzzy c-means text clustering based on topic concept sub-space

To improve the accuracy of text clustering, fuzzy c-means clustering based on topic concept sub-space （TCS2FCM） is introduced for classifying texts. Five evaluation functions are combined to extract key phrases. Concept phrases, as well as the descriptions of final clusters, are presented using WordNet origin from key phrases. Initial centers and membership matrix are the most important factors affecting clustering performance. Orthogonal concept topic sub-spaces are built with the topic concept phrases representing topics of the texts and the initialization of centers and the membership matrix depend on the concept vectors in sub-spaces. The results show that, different from random initialization of traditional fuzzy c-means clustering, the initialization related to text content contributions can improve clustering precision.

An Auto-Grading Oriented Approach for Off-Line Handwritten Organic Cyclic Compound Structure Formulas Recognition

Auto-grading,as an instruction tool,could reduce teachers’workload,provide students with instant feedback and support highly personalized learning.Therefore,this topic attracts considerable attentions from researchers recently.To realize the automatic grading of handwritten chemistry assignments,the problem of chemical notations recognition should be solved first.The recent handwritten chemical notations recognition solutions belonging to the end-to-end trainable category suffered fromthe problem of lacking the accurate alignment information between the input and output.They serve the aim of reading notations into electrical devices to better prepare relevant edocuments instead of auto-grading handwritten assignments.To tackle this limitation to enable the auto-grading of handwritten chemistry assignments at a fine-grained level.In this work,we propose a component-detectionbased approach for recognizing off-line handwritten Organic Cyclic Compound Structure Formulas(OCCSFs).Specifically,we define different components of OCCSFs as objects(including graphical objects and text objects),and adopt the deep learning detector to detect them.Then,regarding the detected text objects,we introduce an improved attention-based encoder-decoder model for text recognition.Finally,with these detection results and the geometric relationships of detected objects,this article designs a holistic algorithm for interpreting the spatial structure of handwritten OCCSFs.The proposedmethod is evaluated on a self-collected data set consisting of 3000 samples and achieves promising results.

Concept Association and Hierarchical Hamming Clustering Model in Text Classification

We propose two models in this paper. The concept of association model is put forward to obtain the co-occurrence relationships among keywords in the documents and the hierarchical Hamming clustering model is used to reduce the dimensionality of the category feature vector space which can solve the problem of the extremely high dimensionality of the documents' feature space. The results of experiment indicate that it can obtain the co-occurrence relations among key-words in the documents which promote the recall of classification system effectively. The hierarchical Hamming clustering model can reduce the dimensionality of the category feature vector efficiently, the size of the vector space is only about 10% of the primary dimensionality. Key words text classification - concept association - hierarchical clustering - hamming clustering CLC number TN 915. 08 Foundation item: Supporteded by the National 863 Project of China (2001AA142160, 2002AA145090)Biography: Su Gui-yang (1974-), male, Ph. D candidate, research direction: information filter and text classification.

An Effective Concept Extraction Method for Improving Text Classification Performance

This paper presents anew way to extract concept that can beused to improve text classification per-formance (precision and recall). Thecomputational measure will be dividedinto two layers. The bottom layercalled document layer is concernedwith extracting the concepts of parti-cular document and the upper layercalled category layer is with findingthe description and subject concepts ofparticular category. The relevant im-plementation algorithm that dramatic-ally decreases the search space is dis-cussed in detail. The experiment basedon real-world data collected from Info-Bank shows that the approach is supe-rior to the traditional ones.

A Heuristic Text Analytic Approach for Classifying Research Articles

Classification of research articles is fundamental to analyze and understand research literature. Underlying concepts from both text analytics and concept mining form a foundation for the development of a quantitative heuristic methodology, the Scale of Theoretical and Applied Research (STAR), for classifying research. STAR demonstrates how concept mining may be used to classify research with respect to its theoretical and applied emphases. This research reports on evaluating the STAR heuristic classifier using the Business Analytics domain, by classifying 774 Business Analytics articles from 23 journals. The results indicate that STAR effectively evaluates overall article content of journals to be consistent with the expert opinion of journal editors with regard to the research type disposition of the respective journals.

Viewing the Introduction of the Da Yan Pagoda from Functional Equivalence Theory

Translation is a trans-cultural communication activity which related to two languages. The main goal of translation is,no doubt, to establish a particular type of correspondence between the source text and the target text. The nature of the correspondence has been referred to"faithfulness"or"fidelity", or more predominantly, the notion of"equivalence".This issue attempts to analyze the brief introduction of the Da Yan Pagoda, which is a famous scene in Xian from the point of functional translation equivalence's view.

Court Sight Translation From Text-Linguistic Approach

Court interpreting as a type of dialogue or liaison interpreting has recently drawn an increasing level of attention in a variety of disciplines, including legal science, applied linguistics, and translation studies. Amongst discussions relevant to court interpreting, the area of sight translation has yet to be emphasized, despite its importance to the outcome of a trial. In this study I first had observations of court interpreting activities on several occasions. Based on these observations, I then formulated a questionnaire and distributed it to 86 interpreters in two training workshops organized by the Taiwan High Court in 2013. The key findings are as follows： most interpreters consider sight translation to be more difficult than other forms of interpretation in the courtroom; while conducting sight translation many interpreters pause in order to seek clarification or are interrupted; most interpreters would prefer the judge or the prosecutor to orally summarize the text to be sight translated; and, after ＂negotiation,＂ most practitioners tend to lower the level of formality when dealing with a text written in a formal style. These findings imply that interpreters conducting sight translation render a translation through ＂negotiation＂ with other participants of the activity; this negotiation can be seen as an attempt to build a ＂context＂ from the perspective of liaison interpreting. This study intends to raise the awareness of court interpreters regarding a number of key issues in sight translation, and the results are hoped to be conducive to the future study of other types of liaison interpreting and interpreting as a whole.

The Analysis of Dover Beach from the Perspective of New Criticism

Many of the literary works of Matthew Arnold reflect the contradictory psychology in the 19th century,of which Dover Beach ranks high..It touches the major concerns of Mid-Victorian writing.Since the readers have good acknowledgement of the extrinsic approach,to analyze this poem from a New Criticism point of view might better and objectively probe the central idea of it.

交替传译场域中两会记者会口译译者群体行为研究

通过阐述译者行为批评理论的描写性,可以推导出口译预设即口译译者行为的描写性。从译者行为批评理论的描写性及群体译者行为这一路径出发,在“文本-行为-社会”评价系统视域中,对口译译者群体行为进行探究,可以建构交替传译场域中的口译译者行为的描写性图式。此外,基于交替传译场域中口译译者群体行为的共性显征,可以得出口译“显文本”双重的动态建构过程及其描写图式,即“潜文本-预设行为-显文本-预设行为-社会”,这一反复在“文本”与“社会”之间的行为,是“语码-译入语文本”及“社会-译入语文本”双重的显文本生成过程。

身份识别信息“使用”的界定纷争——基于美国加重身份盗窃犯罪的判例考察

非法使用个人信息行为的刑法规制问题是当前我国刑法研究的一大热点,但“使用”含义的多重性及极具争议性尚未引起学者们的关注。在最早单独制定身份信息犯罪立法的美国,对于如何理解身份识别信息的“使用”存在宽泛解释和限缩解释之间的严重对立。考察美国加重身份盗窃犯罪的判例,可以发现检方都极力主张宽泛解释,辩方则再三强调限缩解释的必要性,而各联邦巡回上诉法院的判决之间也存在严重分歧。美国最高法院通过杜宾案明确了对“使用”应当采取限缩解释的立场,并提出了“关键所在”标准,而该判决的协同意见则提出了对这一新标准的质疑,认为只有国会立法才能从根本上解决对“使用”的界定争议问题。美国司法实践中对身份识别信息“使用”的界定争议为我国非法使用个人信息的刑法规制研究提供了借鉴。

基于标签增强的细粒度文本分类

文本分类是自然语言处理的一个重要分支,旨在通过训练给数据标注标签。但现有的方法仅仅考虑了标签和文本之间最浅显的语义关系,并没有考虑标签本身的额外语义信息,导致文本分类的准确率难以提升。针对此问题,提出一种基于标签增强的细粒度文本分类模型(FGTC),它根据已知信息对标签进行解释,丰富了标签和文档之间的语义联系。此外,FGTC进一步建模标签中短语的序列关系,并采用单词级别的细粒度标签注意力方法,充分挖掘了标签的有效信息。在四个基准数据集上进行了对比实验,结果表明,该模型在文本分类任务上的准确率得到有效提升。

取旧辞与引古事:萧纲骈文使事用典的文本建构作用

萧纲作品经常引经据典,尤以骈文使事用典为多。萧纲骈文用典以引成辞的语典为主,典事来源范围广泛又重点突出。使事用典是萧纲骈文文本的重要构建手段,无论是掇取旧辞,还是使用古事,都在内容上拓展了萧纲骈文的表现疆域,令其内涵更绚烂多姿,意蕴更深入厚重。引古事取旧辞是萧纲骈文书写的重要手段,不仅是构成文本内容的重要组成部分,在文本的语句熔铸和篇章结构上也具有不可忽视的作用。萧纲骈文使事用典既追摹学习前修时贤典范作品,又求新求变,形成了鲜明的个性特点。

对事实与分析方法的关切——谢尔曼·肯特与孙子情报分析思想的比较研究

[研究目的]谢尔曼·肯特和孙子是西方和中国具有重要影响的情报理论家,通过对二者情报分析思想的比较研究,可作为深入探索中国古代与西方现代情报分析理论之间的异同与联系的有益尝试,有助于重新发掘中国古代情报理论的独特价值。[研究方法]通过文本对比分析法,梳理比较谢尔曼·肯特和孙子对情报分析地位作用的认识,以及各自情报分析方法的异同之处。[研究结论]《孙子兵法》的创作时间虽远早于肯特的情报分析理论形成时期,但其中蕴含的战略情报分析思想却并不逊色,在有些方面甚至有着更为深入和独特的洞见。这表明中国古代的情报理论具有独特的价值和意义,对于当今情报分析工作的发展具有重要的启示作用。

AI生成式文学的创作试验与文本解读

随着ChatGPT技术迭代,AI生成式写作以及由此带来的一系列关于文学本质问题的思考,引发了研究者们的关注,但从目前的成果来看,对AI生成式写作的具体创作试验进行分析和文本解读的文章较少。故文章以首届“中文AI微小说大赛”的六篇获奖作品为例,研究其人机交互式写作的基本策略、当前AI生成式写作过程中的人机交互体验,通过解读AI生成式文学创作的具体文本,分析AI生成式写作带来的文本解读实践中存在的困境。

教育政策研究的理解诠释旨趣及其意蕴

教育政策研究的理解诠释旨趣强调探究教育政策所显示的意义、价值或信念。以理解诠释视角研究教育政策会发现:作为文本的教育政策具有耐久性和距离性,作为话语的教育政策具有建构性和实践性;教育政策具有效果历史意识和历史情境性,与权力具有互构性。教育政策研究者们应充分意识到:教育政策研究对象不只是客观事实,更是充满意义的世界;教育政策研究中不仅要注意时空和社会文化脉络对教育政策的影响,还要关注教育政策与社会问题、社会主体身份的关系;教育政策研究者应具备视域融合的视角,注意教育政策参与的民主性。显然,教育政策研究的理解诠释取向,能够为教育政策研究提供新的视角、问题意识和方法,有助于探明教育政策意义及其传递过程。

基于多模态阐释学的《江格尔》史诗传播与传承形态转变

《江格尔》作为我国三大史诗之一,在中国史诗学研究中具有十分重要的地位。史诗《江格尔》不仅以传统的演唱方式传承,还以印刷文本、图像文本、音视频文本、影视文本、雕塑画廊和文物遗址等多种形式加以传承和传播,不断实现着史诗《江格尔》的创造性转化和创新性发展,以适应新时代弘扬中华优秀传统文化的新要求。史诗《江格尔》这些多种传承和传播方式,构成了其作为中华优秀传统文化遗产的整体存在形态。基于“双创”理念,我们从阐释学研究维度就英雄史诗《江格尔》多模态传承与传播加以理论阐述,指出每一种史诗传承传播形态都有其存在的合理性和必要性,是新时代优秀文化遗产与时俱进的发展趋势,需要客观、科学和辩证的阐述和解读。我们要挖掘其深厚的文化内涵和时代价值,积极为新时代民间文艺学学科体系、学术体系和话语体系的建设贡献一份力量。