文本分类C#实现*

设计并实现一个基于向量空间模型和简单贝叶斯的文本分类系统，系统采用层级多标签的分类策略。详细介绍词语切分统计、终分类器值计算、层级小类校正和兼类判断四个子系统模块。基于向量空间模型分类的第一级大类和层级小类的微平均分别为89.7%和77.8%，简单贝叶斯分别为67.6%和66.5%。     

国史知识的语义揭示与组织方法研究

深入开展中华人民共和国国史的教育和研究一直是各方高度重视的工作。将国史知识进行语义揭示和组织,对于国史的教育和研究具有重要意义。在参考相关研究成果的基础上,本文提出了“向下挖掘,向上组织”的国史知识语义揭示与组织方法。这一方法以国史本体为基础,在对隐藏于国史资源文本条目中的国史知识对象和相关事实进行语义挖掘和揭示的基础之上,通过国史知识对象的关联,构建国史知识网络,并基于时间、类属、层级及统计等关系,对国史知识内容进行更高层次的多维组织展示,并基于这一思路开发了相应的系统平台,实现了国史知识的揭示、重组和其他创新应用。本文所提出的国史知识语义揭示和组织方法对其他类型知识的开发利用具有参考价值。图7。参考文献12。     

语篇衔接手段研究

语篇衔接手段在语篇构建及语篇理解中具有举足轻重的作用,了解并掌握语篇衔接手段对英语学习及英语应用至关重要。通过举例分析,介绍语法衔接手段和词汇衔接手段的特点,研究其在语篇构建中的积极作用及其在实现语意连贯中的效果,以期对英语学习及其应用有所裨益。     

Skopostheorie and the Application to English-Chinese Film Title Translation

This paper aims to explore the film title translation (FTT) from English to Chinese with an attempt to adapt Skopostho?erie as a guiding theory. Although usually short, film titles have a significance ...     

Automatic thematic classification of election manifestos

We digitized three years of Dutch election manifestos annotated by the Dutch political scientist Isaac Lipschits. We used these data to train a classifier that can automatically label new, unseen election manifestos with themes. Having the manifestos in a uniform XML format with all paragraphs annotated with their themes has advantages for both electronic publishing of the data and diachronic comparative data analysis. The data that we created will be disclosed to the public through a search interface. This means that it will be possible to query the data and filter them on themes and parties. We optimized the Lipschits classifier on the task of classifying election manifestos using models trained on earlier years. We built a classifier that is suited for classifying election manifestos from 2002 onwards using the data from the 1980s and 1990s. We evaluated the results by having a domain expert manually assess a sample of the classified data. We found that our automatic classifier obtains the same precision as a human classifier on unseen data. Its recall could be improved by extending the set of themes with newly emerged themes. Thus when using old political texts to classify new texts, work is needed to link and expand the set of themes to newer topics.     

真之统一多元论

塔斯基提出的作为真之定义的T模式,引发了关于“真”的收缩论和膨胀论的争论。文章提出另一种真之定义即T’模式,作为对T模式的补充,从而改进了塔斯基的语言层次论,并将真之收缩论和膨胀论统一起来。在普特南的“内在实在论”的基础上,文章对“存在”和“事实”加以界定,对“内在符合论”给以澄清,并阐明真之实用论和真之融贯论的作用及其关系,从而将真之符合论、实用论和融贯论以及收缩论和膨胀论统一起来。     

Key phrase aware transformer for abstractive summarization

Abstractive summarization aims to generate a concise summary covering salient content from single or multiple text documents. Many recent abstractive summarization methods are built on the transformer model to capture long-range dependencies in the input text and achieve parallelization. In the transformer encoder, calculating attention weights is a crucial step for encoding input documents. Input documents usually contain some key phrases conveying salient information, and it is important to encode these phrases completely. However, existing transformer-based summarization works did not consider key phrases in input when determining attention weights. Consequently, some of the tokens within key phrases only receive small attention weights, which is not conducive to encoding the semantic information of input documents. In this paper, we introduce some prior knowledge of key phrases into the transformer-based summarization model and guide the model to encode key phrases. For the contextual representation of each token in the key phrase, we assume the tokens within the same key phrase make larger contributions compared with other tokens in the input sequence. Based on this assumption, we propose the Key Phrase Aware Transformer (KPAT), a model with the highlighting mechanism in the encoder to assign greater attention weights for tokens within key phrases. Specifically, we first extract key phrases from the input document and score the phrases’ importance. Then we build the block diagonal highlighting matrix to indicate these phrases’ importance scores and positions. To combine self-attention weights with key phrases’ importance scores, we design two structures of highlighting attention for each head and the multi-head highlighting attention. Experimental results on two datasets (Multi-News and PubMed) from different summarization tasks and domains show that our KPAT model significantly outperforms advanced summarization baselines. We conduct more experiments to analyze the impact of each part of our model on the summarization performance and verify the effectiveness of our proposed highlighting mechanism.     

Competing priorities: Singaporean teachers’ perspectives on critical literacy

This paper explores a group of Singaporean English language teachers’ knowledge and beliefs about critical literacy as well as their perspectives on how best to teach literacy and critical literacy in Singapore schools. A face-to-face survey was conducted among 58 English language teachers by using open-ended questions. The survey covered various topics related to literacy instruction including text decoding, meaning construction, and critical analysis of texts. The participating teachers believed strongly that reading and writing are transactional and interactional practices. However, they were less certain in their beliefs about teaching critical literacy including the critical, analytical and evaluative aspects of text reading. Some teachers saw a conflict between using time on teaching critical literacy and preparing students to pass their exams. As critical literacy is not a requirement at exams, they found it difficult to justify using time teaching it. The results suggest that the teachers’ belief systems are strongly influenced by the broad macro-structure of the educational system in Singapore and their own educational experiences.     

文本阐释原理与文献传播研究

文本阐释原理与文献传播研究●周庆山ＡＢＳＴＲＡＣＴＴｈｅｔｈｅｏｒｙｏｆｔｅｘｔｅｘｐｌａｎｎａｔｉｏｎｉｓｐｕｔｆｏｒｗａｒｄｗｈｉｌｅａｎａｌｙｚｉｎｇｔｈｅｓｉｇｎｉｆｉｃａｎｃｅｏｆｔｅｘｔｅｘｐｌａｎａｔｉｏｎｉｎｔｈｅｓｔｕｄｙｏｆｄｏｃ...