An On-line Assessment System for English-Chinese Translation

On-line assessment of English-Chinese translation is a challenging task as it involves natural language processing.YanFa,an on-line assessment system for English-Chinese translation,is a pilot research project into scoring student's translation on-line.Based on the theory of translation equivalence,an algorithm called "conceptual similarity matching" was developed.YanFa can assess students' translation on-line timely,generate test papers automatically,offer standard versions of translation,and the scores of each sentence to students.The evaluation proves that YanFa is practical compared with the scores given by experts.     

试论南通话里的“交关”和“稀”

程度副词是现代汉语程度量的标记词,具有粘着性强、定位性强等特性。文章重点研究了南通话里的"交关"和"稀"这两个程度副词的用法,并指出由于南通特殊的地理位置和南通话在形成过程中的方言交叉影响,"交关"和"稀"在句法功能、语义等方面既具有与现代汉语程度副词相同的特性,又具备一定的特殊性。     

特定领域中语义校对系统的开发

介绍应用于报刊书籍政治性错误校对的一个语义校对软件系统的设计原理和实现过程．本系统先把文本切分成词语，找出敏感词，合并成术语，部分术语通过短语本身或左右片段即可做出正误判断；另一部分术语则用整个句子语义与知识库进行模糊匹配得到它的错误隶属度．     

基于语义相似度的话题关联检测方法

为有效识别任意两篇报道的相似性,提出了一种基于语义相似度的话题关联检测算法.该算法首先通过计算特征词之间的相对熵作为两篇报道中特征词之间的语义相似度;其次,通过计算平均语义相似度获得特征词和报道之间的关联度;最后,结合特征词在语料库中的TF-IF(term frequency-inverse document frequency)权重计算两篇报道之间的关联度,实现报道之间的关联度检测.本文提出的方法与现有的向量空间模型方法和仅依赖于平均点互信息的方法进行了比较,并通过TDT4中文语料进行测评,结果表明,基于语义相似度的关联检测方法能够更好地利用文本的语境信息,提高了现有检测系统的性能,其最小DET(detection error tradeoff)代价降低了3%.      

英文船舶命名特点分析

本文以IMO登记的55450条船名作为语料进行分析,认为船名以1-3词为宜,词汇选择以普通名词和形容词为主,地名人名、动植物、神话人物、星辰星座、臆造词、船舶用途命名为辅,极少使用修辞。     

一种关联多本体的科技奖励检索方法

现有的科技奖励检索都是基于关键词的匹配,忽略了对用户查询的语义理解。针对传统信息检索存在的问题以及结合当前面向实际应用的基于本体的语义检索的特点,提出一种关联多本体的科技奖励检索方法。通过对科技奖励项目的领域本体构建,对概念相似度计算方法的改进及关联多本体概念,使扩展词语更能表达用户检索意图。实验结果表明,该方法对比传统查询检索和单独本体扩展检索获得了更好的召回率和准确率。     

A Semi-automatic Method Based on Statistic for Mandarin Semantic Structures Extraction in Specific Domains

This paper proposed a new method of semi-automatic extraction for semantic structures from unlabelled corpora in specific domains. The approach is statistical in nature. The extracted structures can be used for shallow parsing and semantic labeling. By iteratively extracting new words and clustering words, we get an inital semantic lexicon that groups words of the same semantic meaning together as a class. After that, a bootstrapping algorithm is adopted to extract semantic structures. Then the semantic structures are used to extract new key words and augment the semantic lexicon. The resultant semantic structures are interpreted by persons and are amenable to handediting for refinement. In this experiment, the semi-automatically extracted structures SSA provide recall rate of 84.5%.     

翻译语境对英汉翻译的影响

语境对翻译有着重要的影响,本文从言语、语言、情景、文化语境四个层次,从等效原则的角度,对英汉翻译中译者作品风格、语言、语义、文化等方面的影响进行探讨。     

Generating Domain-Specific Affective Ontology from Chinese Reviews for Sentiment Analysis

Considering the diversities and ambiguities of opinion expressions in Chinese online product reviews,normal sentiment analysis technologies have exposed their inadequateness in both classification accuracy and identifying effectiveness.We propose a novel approach which can easily identify product features and corresponding opinions by building a domain-specific affective ontology and thus mapping comment sentences to the objects defined in the affective ontology.Ontology is created automatically by processing the online reviews;both product features and affective words are presented as nodes which are connected to each other by their semantic relationship.Furthermore,in order to increase the accuracy,we introduce a dynamic polarity detection technique for affective words whose sentimental tendencies are dependent on particular contexts.The experimental results clearly demonstrate the performance improvement of our approach compared with others in real world online product reviews for classification tests.     

注射器针头缺陷在线检测技术与虚拟仪器实现

针对国内绝大部分企业采用人工目视进行一次性注射器针头缺陷检测的现状,开发了一种基于虚拟仪器的针头缺陷在线检测系统。系统通过NI公司的[c]FP-PWM-520模块控制步进电机,利用LabVIEW的IMAQ VISION软件包进行数字图像处理,包括滤波、图像增强、自动阈值化、形态学处理、定位和模板匹配等。试验表明,该系统可以满足目前企业中各种规格的针头缺陷在线检测需求。     

中英思维模式差异对英汉学术论文写作的影响

探讨了中英语篇思维模式差异对英汉学术论文写作中论证方法的影响问题.文章通过分析指出,中英思维模式存在着直觉与抽象、本体与客体和螺旋与直线型差异,并因此导致英汉学术论文中论证方法在修辞手段、引经据典、引用权威等方面的使用差异.文章最后指出,只有了解英汉思维模式的差异,分析其文化成因,才能真正实现跨文化写作的成功.     

桥梁结构在线健康监测预警系统Ⅰ——监测评估预警体系和模块设计

针对不同桥梁的特点,在参照国家有关技术规程规范的要求和相关研究成果的基础上,研究提出了运营桥梁在线健康监测及状态评估的指标体系,讨论了传感器布置的原则及一般的应力、位移传感器布置方案,给出了系统设计的模块框图及顶层数据流程图.所提出的桥梁在线健康监测状态评估的指标体系、结构应力、位移传感器布置及系统的模块设计,对营运中的桥梁监测与养护管理具有重要的指导意义和实用价值.     

半监督卷积神经网络的词义消歧

为了解决有标签语料获取困难的问题，提出了一种半监督学习的卷积神经网络(convolutional neural networks, CNN)汉语词义消歧方法. 首先，提取歧义词左右各2个词汇单元的词形、词性和语义类作为消歧特征，利用词向量工具将消歧特征向量化；然后，对有标签语料进行预处理，获取初始化聚类中心和阈值，同时，使用有标签语料对卷积神经网络消歧模型进行训练，利用优化后的卷积神经网络对无标签语料进行语义分类，选取满足阈值条件的高置信度语料添加到训练语料之中，不断重复上述过程，直到训练语料不再扩大为止；最后，使用SemEval-2007:Task#5作为有标签语料，使用哈尔滨工业大学无标注语料作为无标签语料进行实验. 实验结果表明:所提出方法使CNN的消歧准确率提高了3.1%.      

英语中女性词语义贬降所影射的性别歧视

从历时语言学角度出发,阐述lady,madam,woman,mother,sister,girl,queen,spinster,mistress,governess,hussy,quean,wench,tart等女性词的语义变化过程, 分析探讨英语中女性词语义贬降所影射出的性别歧视现象.     

滑坡灾情数据多层级语义检索方法

如何在海量多源多模态的滑坡灾害时空大数据中快速精准地发现满足灾情评估任务需求的优势信息，是综合减灾救灾的关键. 传统灾害数据检索多以“人工经验+关键字”的被动检索方式为主，难以兼顾任务的精确性与时效性，为此，提出了一种面向评估任务的滑坡灾情数据多层级语义检索方法. 通过建立滑坡灾情评估任务对数据特征需求的显式语义描述及任务需求与数据特征之间的高级语义映射，并据此设计多层级语义匹配的数据检索算法，面向灾情评估任务实现优势数据汇聚. 以四川茂县滑坡灾害评估为例进行实验分析，本文检索方法查询效率具有明显优势，900 km2、90 d范围内的灾情数据精准检索效率达到秒级，且推荐优势数据集的准确性高，60 d时间差距阈值下推荐结果平均贴近度达到90%以上. 结果表明本方法可根据任务需求准确可靠地快速自动获取灾害数据，从而显著提高减灾应急响应能力.      

联大一般性辩论中标记性主位的英汉同传

联合国大会常会分为两个阶段:前段主要为一般性辩论,后段为对其他各项议程项目的讨论和审议。本文旨在讨论联大一般性辩论发言的英汉同声传译对标记性主位的处理策略,包括这些策略在同声传译训练中的适用性及其特点。     

Automatic Multi-Document Summarization Based on Keyword Density and Sentence-Word Graphs

As a fundamental and effective tool for document understanding and organization,multi-document summarization enables better information services by creating concise and informative reports for large collections of documents.In this paper,we propose a sentence-word two layer graph algorithm combining with keyword density to generate the multi-document summarization,known as Graph Keywordρ.The traditional graph methods of multi-document summarization only consider the influence of sentence and word in all documents rather than individual documents.Therefore,we construct multiple word graph and extract right keywords in each document to modify the sentence graph and to improve the significance and richness of the summary.Meanwhile,because of the differences in the words importance in documents,we propose to use keyword density for the summaries to provide rich content while using a small number of words.The experiment results show that the Graph Keywordρ method outperforms the state of the art systems when tested on the Duc2004 data set.     

语料库驱动的心理动词论元结构研究——以口语中五个最常见的心理动词为例

运用功能语法理论,调查统计英国国家语料库中口语最常见的五个心理动词在日常对话中的使用情况,旨在揭示其语义特征,论元搭配和及物性特征,归纳其论元结构并探讨其应用价值.     

Automatic semantic analysis of software requirements through machine learning and ontology approach

Nowadays, software requirements are still mainly analyzed manually, which has many drawbacks (such as a large amount of labor consumption, inefficiency, and even inaccuracy of the results). The problems are even worse in domain analysis scenarios because a large number of requirements from many users need to be analyzed. In this sense, automatic analysis of software requirements can bring benefits to software companies. For this purpose, we proposed an approach to automatically analyze software requirement specifications (SRSs) and extract the semantic information. In this approach, a machine learning and ontology based semantic role labeling (SRL) method was used. First of all, some common verbs were calculated from SRS documents in the E-commerce domain, and then semantic frames were designed for those verbs. Based on the frames, sentences from SRSs were selected and labeled manually, and the labeled sentences were used as training examples in the machine learning stage. Besides the training examples labeled with semantic roles, external ontology knowledge was used to relieve the data sparsity problem and obtain reliable results. Based on the SemCor and WordNet corpus, the senses of nouns and verbs were identified in a sequential manner through the K-nearest neighbor approach. Then the senses of the verbs were used to identify the frame types. After that, we trained the SRL labeling classifier with the maximum entropy method, in which we added some new features based on word sense, such as the hypernyms and hyponyms of the word senses in the ontology. Experimental results show that this new approach for automatic functional requirements analysis is effective.