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   lexical knowledge 的翻译结果: 查询用时:0.176秒
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lexical knowledge
相关语句
  词汇知识
     Three Phases of Understanding Lexical Knowledge and its Implications for College English Vocabulary Teaching and Learning
     理解词汇知识的三个阶段对大学英语词汇教学的启示
短句来源
     Lexical Knowledge Discovery for Information Retrieval
     面向信息检索的词汇知识发现
短句来源
     A Formal Representation of Russian Lexical Knowledge
     俄语词汇知识的形式表达
短句来源
     Representation of Lexical Knowledge in Electronic Dictionary
     电子词典与词汇知识表达
短句来源
     Lexical knowledge representation and knowledge extraction are bottlenecks of natural language processing.
     词汇知识的表达与取得是自然语言处理极须克服的问题 ,本论文提出一个初步的架构与常识的抽取机制。
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  “lexical knowledge”译为未确定词的双语例句
     3. The semantic, syntax and lexical knowledge representation model are built.
     3.首次建立了作战文书生成中的语义、语法、词汇等知识的表示模型。
短句来源
     The world knowledge needed in the algorithm is included in Ontology, and lexical knowledge in the Semantic Lexicon.
     算法中需要的世界知识和汉语词级知识分别包含在Ontology和语义词典中。
短句来源
     and that learners' depth of lexical knowledge becomes greater with their increase in vocabulary size but for learners with different vocabulary sizes, there is disproportionate development in their depth of lexical knowledge.
     3 )词汇深度知识随着词汇广度知识的增长而增长 ,但对不同词汇水平的学习者来说 ,其词汇深度知识的发展极不平衡。
短句来源
     The thesis empirically explores the role of implicit and explicit learning in the construction of lexical knowledge in the course of reading.
     从实证角度出发,本研究深入探究了第二语言学习者在词汇附带习得中的外显学习与内隐学习,及词汇量不同的学习者在猜测词义和词汇附带习得中的差异。
短句来源
     Collocation is an important part in applied linguistics and one aspect of profound lexical knowledge .
     词语搭配是词汇深度知识的一个方面,是高年级的第二语言习得者语言输出时面临的最大问题之一。
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  相似匹配句对
     On Deepening of Lexical Knowledge for English Majors
     英语专业词汇教学中的词汇知识深化问题
短句来源
     Lexical Knowledge Discovery for Information Retrieval
     面向信息检索的词汇知识发现
短句来源
     On knowledge marketing
     论知识营销
短句来源
     On the Explicit Knowledge
     论非嵌入编码知识
短句来源
     On Lexical Ambiguit
     浅析词汇歧义现象
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  lexical knowledge
The system exhibited a substantial ability to interpret cursive connected strings without recourse to lexical knowledge.
      
In addition, we empirically analyze the effects of providing the classifier with background knowledge in form of user defined profiles and examine the use of lexical knowledge for feature selection.
      
These findings suggest that certain principles of knowledge representation common to theories of lexical knowledge-such as overlapping and distributed representations-also characterize grammatical knowledge.
      
We show how we can use these contexts in default logic to identify lexical knowledge about the query word such as synonyms, antonyms, specializations, meronyms, and more sophisticated first-order semantic knowledge.
      
In the dex framework, a word for which lexical knowledge is sought is called a query word.
      
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L2 vocabulary acquisition research is still a very weak subfield of SLA in China.This paper is meant to clarify the theoretical bases of L2 vocabulary acquisition by defining or redefining lexicon, vocabulary size, lexical categories,lexical knowledge as well as its acquisition. The author also points out some issues such as creation of nonwords and lexical attrition which demand attention in this field.

第二语言词汇习得研究在我国还是一个薄弱环节。本文旨在阐明这一领域的理论基础 :(个人 )词汇量、词汇类型、心理词汇、词汇知识及词汇习得。作者指出 ,除以上几个方面外 ,还有生造非词、词汇知识耗损等相关现象亟待研究

This is a cross_sectional quantitative research on L2 vocabulary depth (or knowledge) across Chinese EFL learners of four different proficiency levels. The present paper has its focus on the two dimensions(or types)of word knowledge: meaning and affix. It aims to find out and offer a clear illustration of the possible developmental routes or characteristic patterns of lexical knowledge of English high_frequency words in terms of 'productive' vs. 'receptive' abilities. The results are analyzed on the statistic...

This is a cross_sectional quantitative research on L2 vocabulary depth (or knowledge) across Chinese EFL learners of four different proficiency levels. The present paper has its focus on the two dimensions(or types)of word knowledge: meaning and affix. It aims to find out and offer a clear illustration of the possible developmental routes or characteristic patterns of lexical knowledge of English high_frequency words in terms of 'productive' vs. 'receptive' abilities. The results are analyzed on the statistic basis and some speculations are put forward.

本文是对课堂环境下二语词汇深度 (vocabularydepth)习得或二语词汇知识 (wordknowl edge)习得的横向调查。本研究力图从“深度”的层面来探索二语词汇知识 (如意义、词缀 )习得的发展路径或具体特征。本文的受试分别代表了四种不同英语水平的学习群体。然而 ,他们在接受本研究 1 0个高频词深度习得检测中所获得的结果却反映了二语词汇知识习得的复杂性和不一致性。本研究结果及发现不仅能弥补“宽度”研究的不足 ,而且对现时的外语教学、二语习得及词汇习得理论的建立具有一定的启发作用。

Traditional models of content based information filtering are clumsy to describe the complex relationships of events that affect filtering process. Furthermore, it is difficult for users to interact with the filtering system. To address the above problems, BMIF-an information filtering model founded on Bayesian network is proposed in this paper. It firstly outlines the relationship of features, interests, queries and other main elements in information filtering with a simplified Bayesian network, and then provides...

Traditional models of content based information filtering are clumsy to describe the complex relationships of events that affect filtering process. Furthermore, it is difficult for users to interact with the filtering system. To address the above problems, BMIF-an information filtering model founded on Bayesian network is proposed in this paper. It firstly outlines the relationship of features, interests, queries and other main elements in information filtering with a simplified Bayesian network, and then provides six elementary nodes to characterize the relationships in specific conditions. Some use cases of BMIF are presented as well, which includes: ① Describing traditional models with BMIF; ② Adding lexical knowledge to BMIF; ③ Mixing learning with interaction, and combining content based filtering with collaborative filtering.

传统信息过滤模型很难描述对信息过滤结果产生影响的各种因素 ,如质量、内容、用户偏好之间复杂的关系 ,也无合适的方法让用户将知识加入到信息过滤系统中 .因此 ,提出了基于贝叶斯网络的信息过滤模型 BMIF(Bayesian m odel of inform ation filtering) .BMIF是贝叶斯网络的简化 ,它描述了信息过滤的基本结构 ,提供了 6种节点用于描述影响信息过滤的事件之间的关系 .在此基础上 ,提供了 BMIF的各种使用方法 ,包括将传统方法使用BMIF描述 ,将词法知识用 BMIF表示 ,以及将自动学习与手动交互结合 ,将合作过滤与内容过滤结合等

 
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