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研究提高翻译算法的翻译准确性问题。由于英语名词短语语法复杂、规则多,导致传统机器翻译算法存在效率低、准确率不高难题。为提高英语名词短语识别准确率,提出一种粗糙集的名词短语识别方法。粗糙集方法把英语名词短语识别当成一个决策问题,通过粗糙集理论对特征约简和规则优化,最后对其进行进识别。采用粗糙集方法对WSJ英语名词短语样本进行仿真实验,仿真结果表明,粗糙集的名词短语识别正确率高于其它翻译方法,是一种有效英语名词短语机器识别方法。为实际设计提供依据。 相似文献
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机器翻译中,介词短语的附着最能引起句法分析歧义。传统语法将介词短语的附着看成是二元问题。本文在系统功能语法的指导下,将介词短语附着问题转化为三元问题。统计自建的商务英语双语语料库发现,介词短语的第三类附着也大量存在,值得区分。 相似文献
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介词结构类状语和环境要素类状语与能愿动词的位置关系的常式与变式是错序产生的主要区域。在能愿动词句中,介词结构类状语总是与它后面的谓词联系更紧密,它们组成更大的结构,作为相对独立的语法单位与其它部分组配成句。环境要素类状语的位置比较灵活,含有这类状语的能愿动词句的可行性模式比较复杂,外国学生因而无法选择最恰当的语句模式进行表述。 相似文献
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分析和研究了谓词逻辑在ATM上的应用。分别介绍了谓词演算的含义、ATM系统原理和怎样利用谓词逻辑将ATM系统形式化。通过谓词演算、加锁协议等方法,对ATM取款流程进行了形式化描述,建立ATM的四备规则,保证了ATM的安全性和有效性。 相似文献
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在公式集中定义了每个公式的真度其实也就给出了公式集上的一个内蕴模糊子集。本文在二值谓词逻辑系统中引入一类特殊解释,即论域有限的解释,给出了一阶谓词公式A的相对于某一个特定解释下的相对真度定义,从而得到谓词公式集的一类内蕴模糊子集。并证明了这种相对真度也具有与命题逻辑系统中公式的真度相应的某些性质,如MP规则与HS规则。本文为建立谓词逻辑系统中的近似推理理论提供了理论基础。 相似文献
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通过为PKI系统建立信任模型,可以更好地了解这一复杂信任体系中各实体间信任关系建立的过程.在现有模型的基础上,引入更加符合真实应用环境的谓词逻辑和信任参数,扩展了原有模型信任推导方法,并给出了新方法下的认证规则和信任规则.同时结合信任度概率模型,分析了各代表性PKI架构信任传递的过程,以及系统架构对实体间信任度的影响.分析的结果对于构建真实应用环境下的PKI系统有一定指导意义. 相似文献
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论文通过一种常见的“压缩法”,对定语从句复合句中从句的压缩进行了深入的分析。在翻译定语从句的过程中,会因句子结构复杂而无从下手,这时适当地对定语从句进行压缩,找出句子主干或把定语从句压缩成一个简单句就会容易得多。有些定语从句可以缩略为各种短语如：分词短语、形容词短语、介词短语及动词不定式短语等,且句意不受影响。研究定语从句的缩略有两点益处：一是丰富写作风格,提高翻译和语言表达能力,因为它能使我们学会用不同的方法来表达同一思想;二是提高阅读速度和阅读理解能力,因为在阅读中经常会遇到一些定语从句。 相似文献
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科技期刊论文英文标题抽象名词短语结构分析与应用 总被引：1，自引：1，他引：0
本文旨在发现与归纳科技期刊英文标题中"名词+of+名词"结构的语言特点。运用语料库语言学研究方法对理科类科技期刊英文标题进行了大样本统计分析。结果显示,84.5%的英文标题是名词短语形式,以"中心名词+介词短语"的形式最为典型。中心名词主要表现为五类抽象名词。结论表明以抽象名词为中心名词的短语结构因其结构简洁、信息载荷量大而成为科技期刊英文标题的主要表达手段。 相似文献
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词汇是英语学习的基础,词汇搭配的学习对学习者至关重要。英国语言学家威尔金斯（D,Wilkins）说过,“没有语法,人们可以表达的事物寥寥无几;而没有词汇,人们则无法表达任何事物。”英语词汇具有很强的搭配能力,利用英语词汇搭配,可以扩大词汇量,掌握单词的正确用法。本文主要探讨了什么是词汇搭配,词汇搭配的重要性以及英语中词汇搭配的教学实践,以期帮助英语学习者更有效地掌握英语词汇和语言。 相似文献
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We demonstrate effective new methods of document ranking based on lexical cohesive relationships between query terms. The proposed methods rely solely on the lexical relationships between original query terms, and do not involve query expansion or relevance feedback. Two types of lexical cohesive relationship information between query terms are used in document ranking: short-distance collocation relationship between query terms, and long-distance relationship, determined by the collocation of query terms with other words. The methods are evaluated on TREC corpora, and show improvements over baseline systems. 相似文献
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在线词汇资源FrameNet的语义类型对于深层次的自然语言理解具有重要的作用。文章首先对FrameNet的语义类型功能进行论述,指出其由框架类型、本体类型和词汇类型构成,从概念、感情、搭配等层面描述词汇固有的词类特征和语义特征。在此基础上,作者探讨语义类型在自然语言处理中的具体应用范围:如限制框架元素的取值范围,进行问答、文摘、复述和翻译等自然语言理解,便于概念检索中关系相关度的计算,实现语义层面的推理,建立与其他本体在多领域中的映射等。 相似文献
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Takashi Maeda Yoshio Momouchi Hajime Sawamura 《Information processing & management》1980,16(3):119-127
A new method is described to extract significant phrases in the title and the abstract of scientific or technical documents. The method is based upon a text structure analysis and uses a relatively small dictionary. The dictionary has been constructed based on the knowledge about concepts in the field of science or technology and some lexical knowledge, for significant phrases and their component items may be used in different meanings among the fields. A text analysis approach has been applied to select significant phrases as substantial and semantic information carriers of the contents of the abstract.The results of the experiment for five sets of documents have shown that the significant phrases are effectively extracted in all cases, and the number of them for every document and the processing time is fairly satisfactory. The information representation of the document, partly using the method, is discussed with relation to the construction of the document information retrieval system. 相似文献
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[目的]探讨地理学期刊论文英文题名在句法结构和常用表达方面的撰写特点,提高我国期刊论文英译题名的质量。[方法]选取地理学中、外权威期刊2008-2012年间的2000个题名,以国际期刊为参照,对比分析我国英文题名的句法结构及常用表达特点。[结果]与国际期刊相比,我国地理学英文题名句法结构单一,过多使用名词短语结构,复合式题名与动名词短语类使用偏少;常用表达方面,某些学术套语出现率高。[结论]我国英文题名不够简洁,减弱了题名的信息性与吸引性功能。建议期刊编辑和论文作者在英译题名时注意句法结构的多样性,尽量减少母语表达习惯的影响。 相似文献
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《Information processing & management》2001,37(2):199-220
This study proposes a probabilistic model for automatically extracting English noun phrases without part-of-speech tagging or any syntactic analysis. The technique is based on a Markov model, whose initial parameters are estimated by a phrase lookup program with a phrase dictionary, then optimized by a set of maximum entropy (ME) parameters for a set of morphological features. Using the Viterbi algorithm with the trained Markov model, the program can dynamically extract noun phrases from input text. Experiments show that this technique is of comparable effectiveness with the best existing techniques. 相似文献
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《Information processing & management》2022,59(5):103000
Professional discourse is the language used by specialists, such as lawyers, doctors and academics, to communicate the knowledge and assumptions associated with their respective fields. Professional discourse can be especially difficult for non-specialists to understand due to the lexical ambiguity of commonplace words that have a different or more specific meaning within a specialist domain. This phenomena also makes it harder for specialists to communicate with the general public because they are similarly unaware of the potential for misunderstandings.In this article, we present an approach for detecting domain terms with lexical ambiguity versus everyday English. We demonstrate the efficacy of our approach with three case studies in statistics, law and biomedicine. In all case studies, we identify domain terms with a precision@100 greater than 0.9, outperforming the best performing baseline by 18.1–91.7%. Most importantly, we show this ranking is broadly consistent with semantic differences. Our results highlight the difficulties that existing semantic difference methods have in the cross-domain setting, which rank non-domain terms highly due to noise or biases in the data. We additionally show that our approach generalizes to short phrases and investigate its data efficiency by varying the number of labeled examples. 相似文献
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Chengsen Ru Jintao Tang Shasha Li Songxian Xie Ting Wang 《Information processing & management》2018,54(4):593-608
Distant supervision (DS) has the advantage of automatically generating large amounts of labelled training data and has been widely used for relation extraction. However, there are usually many wrong labels in the automatically labelled data in distant supervision (Riedel, Yao, & McCallum, 2010). This paper presents a novel method to reduce the wrong labels. The proposed method uses the semantic Jaccard with word embedding to measure the semantic similarity between the relation phrase in the knowledge base and the dependency phrases between two entities in a sentence to filter the wrong labels. In the process of reducing wrong labels, the semantic Jaccard algorithm selects a core dependency phrase to represent the candidate relation in a sentence, which can capture features for relation classification and avoid the negative impact from irrelevant term sequences that previous neural network models of relation extraction often suffer. In the process of relation classification, the core dependency phrases are also used as the input of a convolutional neural network (CNN) for relation classification. The experimental results show that compared with the methods using original DS data, the methods using filtered DS data performed much better in relation extraction. It indicates that the semantic similarity based method is effective in reducing wrong labels. The relation extraction performance of the CNN model using the core dependency phrases as input is the best of all, which indicates that using the core dependency phrases as input of CNN is enough to capture the features for relation classification and could avoid negative impact from irrelevant terms. 相似文献
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英语口语语法形成的主要因素有三个：口语语境、即时产生话语的限制以及口语的交互性／人际性．受这些因素的影响,口语语法呈现出如下主要特征：省略、代词、小品词、名词短语、相邻语对、共构单位、问句以及祈使句的高频使用;词汇密度小;有限的词汇使用量;话语不流畅以及语法结构简单化．理解和掌握英语口语语法对于英语教学具有重要意义． 相似文献