A Study on Parts of Speech Conversion in English and Chinese from the Perspective of Translation

Parts of speech conversion refers to transforming the certain words of the source language into another category words of the target language, which is one of the common methods and techniques used in the translation of English and Chinese languages. This paper starts from a relatively significant difference in English and Chinese language— the tendency of static words in English in contrast to that of dynamic words in Chinese, to explore the theoretical basis of transference in parts of speech in English and Chinese language translation. Combining with a large number of examples, the author puts forward some skills on transformation of parts of speech in English-Chinese translation to guide translation practice. The study found that the theoretical basis of the conversion in English and Chinese mostly including:1) there is a boundary ambiguity between lexical category;2)English SV/SVO structure is rigorous, which leads to expressing the dynamic meaning by means of using other lexical category; 3) the development of social culture not only makes new words continue to increase rapidly, but also gives many used words with new meanings; 4)it is acknowledged in Lexical morphology that English words which come from derivation are in larger number and derivations can make the word class of the corresponding original words either the same or different. The dynamic and specific features of Chinese make it more use of verbs in language use. Thus, in the process of translation, appropriate parts of speech conversion can make the translation more in line with their own habits of expression.

Animal Words: Parts of Speech and Metaphoricity

The study in this paper belongs to the field of the grammar of metaphor. Six types of animal words were investigated in order to find the connection between their parts of speech and metaphorical relationship by applying the British National Corpus in combination with Collins Dictionary. It is found that not all verbs formed via conversion from nominal animal words carry the conceptual features of the animal entities, and in this case, the resultant verbs do not form metaphors. Where the verbs carry over the conceptual features of the nominal animal words, metaphors will occur. Of course, there are a few exceptions, like fish in fish for, which forms a metaphor though fish as a verb here does not carry over the conceptual features of the nominal fish.As to adjectives and adverbs derived from nominal animal words, they form metaphors in most cases by carrying over the conceptual features of the relevant animals. The study can be broadened to other entity nouns in order to find regularities about when their derivatives form metaphoricity.

On the Conversion of Parts of Speech in English-Chinese Translation

Conversion refers to the transformation of parts of speech in some words while maintaining the original content unchanged in order to make the translated text sound smooth and fluent as well as more idiomatic in the target language. In E-C translation, conversion of pars of speech is one of the most important translation methods. Several different forms about conversion of parts of speech are introduced through analyzing the differences and usages between the two languages so that a better version in E-C translation can be got.

Improve Neural Machine Translation by Building Word Vector with Part of Speech

Neural Machine Translation(NMT)based system is an important technology for translation applications.However,there is plenty of rooms for the improvement of NMT.In the process of NMT,traditional word vector cannot distinguish the same words under different parts of speech(POS).Aiming to alleviate this problem,this paper proposed a new word vector training method based on POS feature.It can efficiently improve the quality of translation by adding POS feature to the training process of word vectors.In the experiments,we conducted extensive experiments to evaluate our methods.The experimental result shows that the proposed method is beneficial to improve the quality of translation from English into Chinese.

A New Part-of-Speech Tagging System Based on Closed-words,Word Form and Rules

A method of part-of-speech tagging of English text based on closed-words, wold-form and rules, its abstract model and formal description of its realizing procedure are presented. Finally, an experimental example is givento illustrate the application of this method.

A Comparative Study of the Usage of Vague Expressions in English and Chinese Cosmetic Advertisements

Vagueness is one of the basic characteristic of natural language. Vague language is employed widely in advertising language. In this research cosmetic advertisements in Chinese and English magazines are selected and analyzed. The results show that in Chinese and English cosmetic advertisements vague adjectives are the most frequently adopted, and that vague nouns and verbs are employed greatly. Comparatives, superlatives, hedges, numerals, quantifiers and pronouns are also used in advertisements.

A Study on Comparison of Words in Ancient and Modern Chinese and Foreign Fantasy Novels

Fantasy novel is a kind of novel literature, which is different from other fictions. With the passage of time, fantasy novels have great development with human society. There are differences and similarities between Chinese and Western fantasy novels,which make literary works widely spread and popular. This study uses corpus linguistics software(Tree-Tagger, Range) to analyze four famous Chinese and English fantasy novels and their English translation, observing the different of proportion of noun, verb,adverb and adjective and the lexical difficulty of the novel.

Mixed-Fisher特征云模型聚类在文本情感分类中的应用

海量网络信息的出现,使得提取文本信息情感观点成为研究的热点。针对文本情感分类中文本信息模糊及分类准确率低的问题,提出了一种基于Mixed-Fisher特征选择的文本云向量模型聚类算法。该算法首先分别计算文档中各个词性特征项的Fisher判别比,根据Fisher判别比越大特征向量判别性越强的Fisher准则,选择Fisher比值较大的前q个特征,并按照词性进行组合生成文档的Mixed-Fisher特征向量。然后在Mixed-Fisher特征向量集上构建文档的云向量模型,根据云向量模型间的差异度对模型进行聚类和合并。将该算法应用于文本情感观点的分类,选择核Fisher判别技术用于最终文本观点的判定。仿真实验结果表明,基于Mixed-Fisher特征的云向量聚类模型的分类准确率明显优于传统向量空间模型,从而验证了核Fisher判别技术的有效性。

基于OBE理念的发电厂电气部分课程建设

发电厂电气部分是电气工程及其自动化专业重要的专业课程,对学生工程实践能力的培养起到重要的支撑作用。该文基于成果导向教育理念(OBE),建立MOOC教学平台的“课前-课中-课后”线上线下混合式闭环教学模式,构建丰富的教学资源,课程教学目标支撑毕业要求,构建成果导向的课程考核评价体系,体现以学生学习为中心。在新的教学模式下,学生学习效果明显改善。在OBE理念指导下,通过MOOC平台进行电气类专业课程改革是改进教学方法、提升教学质量的有效手段,也是未来教学改革的方向。

俄罗斯认知话语范式理论阐释与应用探索

俄罗斯著名语言学家Е.С.库布里亚科娃基于苏俄心理语言学、称名学和语义学理论,在融合西方认知语言学思想的基础上,提出认知话语范式概念,主要用于俄语词类研究。该范式体现出鲜明的俄罗斯语言学研究特色,具有重要的理论和应用价值。目前国内学界对认知话语范式引介与研究尚处于起步阶段。认知话语范式主张,语言现象应从认知和话语两个维度分析,并在两者的映射关系中深入挖掘语言现象背后的学理依据。本文尝试深入解释认知话语范式概念内涵和理论价值,并揭示其在语言现象实证分析中的方法论价值,探索认知话语范式本土化路径,希冀为其他语言,尤其是汉语词类研究提供借鉴。

基于深度学习的设施甜樱桃水肥一体化智能控制系统

水肥一体化技术在现代农业种植中的应用越来越广泛,但目前甜樱桃水肥一体化技术存在缺乏智能控制系统、实时施肥策略指导等问题,为此设计了一种甜樱桃水肥一体化智能控制系统。首先通过词性标注完成了对甜樱桃水肥领域知识实体的信息提取,结合领域知识定义相关概念的类和属性,构建甜樱桃水肥本体模型。引入了一种基于深度学习的甜樱桃水肥领域文本相似度计算模型,在基于深度学习的相似度计算模型的基础上,提出了基于甜樱桃水肥领域综合属性的相似度计算、基于甜樱桃本体语义的相似度计算和甜樱桃水肥策略实例的相似度计算。综合甜樱桃水肥策略实例的地域、果树品种、目标产量以及果树生长时期等属性因素建立了甜樱桃水肥策略库,以Drools规则引擎结合基于深度学习的相似度计算作为推理机制,最终搭建出甜樱桃水肥一体化智能控制系统。

基于注意时序网络的中文词性标注方法

针对传统的基于统计与规则的词性标注模型存在的人工特征依赖、字向量表征单一、特征提取不全面等问题,提出一种有效的基于注意时序网络的中文词性标注模型。对原始的TCN模型结构进行三点改进,并提出将注意时序网络与BiLSTM模型融合到词性标注方法中。上述模型首先通过XLNet模型获取字级别的上下文表示,利用注意时序网络的因果卷积结构获取更高层次的文本序列特征并通过注意力机制优化特征,最后通过BiLSTM进一步学习序列上下文特征,提高词性标注的准确度。实验表明,上述模型性能相较于其它模型有明显提升。

单组分电炉镍渣基地聚物修补材料制备与性能调控

为利用具有潜在活性的固体废弃物电炉镍渣,制备单组分电炉镍渣基地聚物修补砂浆.基于正交实验和极差分析,通过掺入掺合料并改变碱模数和碱当量等关键影响因素,对地聚物砂浆各项修补性能进行调控,获取满足修补性能的最优配合比,确定各因素对修补性能的影响主次.结果表明,最优配比是矿渣掺量为30%,粉煤灰掺量为30%,碱模数为1.2,碱当量为6.5%,其28 d抗压、抗折强度分别为90.29、9.23 MPa,干燥收缩率为0.56×10-3,14 d拉伸粘结强度为3.64 MPa,满足修补砂浆规范要求.经比较,矿渣掺量对修补砂浆性能调控影响最为显著.

融合词性与语义相关性的图书馆智能咨询系统问句相似性计算方法研究

[目的/意义]提高问句相似性计算的准确性,对改善图书馆智能咨询的实际效果具有重要作用。[方法/过程]引入特征词在问句之间的语义相关性指标,提出了融合词性与语义相关性的问句相似性计算方法。首先构建咨询领域专业词典以增强问句处理的业务针对性,然后提出特征词词性权重和语义相关性权重度量方法,并融合两者度量词语在问句中的作用以构建问句语义表征向量,最后采用余弦函数计算问句相似度。[结果/结论]实验表明综合词性与语义相关性特征能有效识别问句中的核心特征词,本文提出的问句相似性计算方法比传统方法具有更高的ACC@1和ACC@3准确率。

现代汉语兼类现象批评认知及常态化研究策略

现代汉语兼类现象是一种客观存在于语言事实中动态变化的语法现象。兼类现象的研究往往依赖于《现代汉语词典》,而《现代汉语词典》兼类词词类标注的缺失表明:兼类词只是兼类现象在词典里的部分反映,是兼类现象的子集,二者的不平衡动态关系受到了词典周期性修订、词频的动态监测及对词类活用认知的制约。因此,现阶段兼类现象外延全貌为:词典里的兼类、当下未收录进词典的兼类、活用产生的临时兼类。兼类现象的常态化研究策略可以还原一个更真实的现代汉语兼类情况。

徽语语法研究综述

1987年《中国语言地图集》中把徽语独立为一个大方言区后,徽语受到了极大重视,徽语的语法研究取得了相当可观的成果。文章整理前人在徽语语法研究方面的成果,从词法、词类、句法和范畴研究四个方面进行综述,对徽语语法研究的未来发展进行展望,为后续研究提供参考。

词类标注对词典释义的促进作用

词类标注和词典释义有着密切的关系。从词类标注的视角来审视词典释义,更容易发现释义中以前不易发现的问题,可以使释义更加严谨、更加精细化,从而促进词典释义的质量提高。本文从词目和释义词语的语法属性的一致性、动词和形容词义项的增补、虚词释义的修改、冗余义项的删除四个方面对此予以阐述。每个方面选取若干条目,这些条目都是因词类标注而发现释义存在问题,从而对释义做出了相应的修订。通过对它们的修订来具体说明词类标注对词典释义的促进作用。

基于跨阶段特征融合算法的混合部位运动图像超分辨率修复方法

混合部位运动图像存在模糊、失真、低分辨率等问题,且峰值信噪比差值较小。提出基于跨阶段特征融合算法的混合部位运动图像超分辨率修复方法。结合非线性映射关系重构像素点,采用跨阶段特征融合算法,完成混合部位运动图像超分辨率修复。实验结果表明:得到完整的混合部位运动图像修复结果,表现出的峰值信噪比差值较大,修复后的图像分辨率更优,满足了混合部位运动图像的现实应用需求。

基于句法依赖增强图的方面级情感分析

方面级情感分析旨在分析句子中特定方面的情感极性,现有研究侧重于利用图神经网络建模上下文与方面的依赖信息,忽略了对上下文中情感词及其词性的挖掘和利用。为此,提出一种基于句法依赖的增强图(syntactic dependency enhancement graph, SDEG)模型,在原始句法依赖图上引入情感知识和词性信息,增强情感词权重和相关词性单词在上下文中的作用。使用双向长短期记忆网络和卷积神经网络捕捉句子的重点语义信息,通过图卷积神经网络建模句法依赖增强图,通过交互注意力机制生成特定方面的上下文语义和语法表示以进行情感极性分类。在多个公共基准数据集上的实验结果表明,所提模型在性能上有明显提升。