natural language text
英 [ˈnætʃrəl ˈlæŋɡwɪdʒ tekst]
美 [ˈnætʃrəl ˈlæŋɡwɪdʒ tekst]
网络 自然语言正文
双语例句
- Research of Natural Language Understanding of Psychology in the Short Text Classification
自然语言理解心理学在短文本分类中的实证研究 - The difference between regular data mining and text mining is that in text mining the patterns are extracted from natural language text rather than from structured databases of facts.
文本数据挖掘也不同于常规意义上的数据挖掘，常规数据挖掘是在数据库中发现感兴趣的模式，而文本数据挖掘是从自然语言文本中发现模式。 - There are four typical kinds of methods to generate natural language: canned text, template-based, phrase-based, and feature-based, and they are all designed for English originally.
目前世界上典型通用的语言生成方法大致有四种：封装文本，基于模板，基于短语以及基于特征的方法。 - The original knowledge which is described in natural language in electronic text is disposed by filtrating, semantic block segmenting, word segmenting, syntax and semantic analyzing, pattern matching. In the end it is expressed in the semantic network and storaged in the multimedia knowledge database.
在本系统中，原始的以电子文本形式存在的自然语言描述的知识经过过滤，切分语义块，分词及语法、语义分析，模式匹配，以语义网络的形式存入多媒体数据库。 - This technology is very useful in natural language understanding, text indexing and language model building, etc.
该技术在语言理解、文本自动索引以及语言模型的建立等方面都有重要意义。 - The method detoures difficulties of word segmentation in the natural language processing, and uses the keywords in the keyword list to matching the natural language text in order to get the keyword combination, to realize answering the question that is asked with natural language.
该方法绕开自然语言分词困扰，采用关键词表中的关键词匹配自然语言文本，获得全文检索的关键词组合，实现对自然语言提问的解答。 - The acquisition of knowledge from natural language text is a very important application of NLP. This technique has great prospect because it can help people search and acquire knowledge efficiently.
从各种自然语言文本中获取知识是自然语言处理技术的重要应用，能有效地帮助人们搜索、获取知识，具有较大的应用前景。 - This paper introduced a knowledge representation model for multilingual natural language text generation system.
介绍了在多语种自然语言生成系统中如何用统一的模型来表示各语种的语言知识。 - A Survey on Natural Language Text Copy Detection
自然语言文档复制检测研究综述 - This technology is an integrated application of many natural language processing techniques, including text preprocessing, text structure analysis, inter-text inference and so on.
该技术是许多自然语言处理技术的综合运用，涉及的内容包括文本预处理、文本结构分析、篇章关联推导等。 - The similarities shown by conjunct heads will help the automatic identification of nominal coordinate structures in natural language text processing.
并列成分中心语语义相似这一特性将帮助计算机自动识别出文本中的名词性并列结构。 - In recent years, SVM was applied to many Natural Language Processing tasks, like Text classification, shallow parsing and Chinese proper nouns recognition, and satisfying results were reported.
目前，支持向量机已经应用于自然语言处理的许多领域，如文本分类，浅层句法分析，专名识别等，都取得了不错的效果。 - E. receiving the unconstrained natural language instruction in the form of text from PC and extracting the linguistic unit which is necessary to the vehicle traveling process, and converts it to the standard format command which is necessary to the vehicle.
即从PC端接收到的不受约束的自然语言文本指令中抽取出控制车辆行驶所必需的各个语言单元，并将其转换为控制车辆所必需的格式。 - As natural language watermarking is regardless of text document formats, it has a wider application prospect.
由于和具体的文本格式无关，这种技术有着更大的应用前景。 - So far, the text steganography techniques have been sufficiently studied and become more and more practical. Natural language steganography represents the trends of text steganography.
目前，文本中的信息隐藏技术研究已经日趋实用，其中自然语言信息隐藏技术代表了文本信息隐藏的发展趋势。 - According to Schank, schema helps people deal with natural language so that they can understand the text well.
Schank（1997）认为，图式有利于人们处理自然语言，达到理解文本的目的。 - In this paper, using the characteristics of Chinese natural language text after a wide range of research, a way to use the basic features of the text hidden text method is designed.
本文对中文自然语言文本的特点进行了广泛的研究，设计了一种利用文本基本特征的文本信息隐藏的方法。 - The first one is using some language rules to analyses the relationship in all components of natural language text.
一种是利用各种语言规则对自然语句进行分析，得到句中各组成成分间的关系结构。 - Term extraction is an important technology and has a wide range of applications in the field of natural language processing, text mining, ontology building, lexicographers and machine translation and so on.
它是信息处理领域的一项重要技术，在自然语言处理、文本挖掘、本体构建、词典编撰、机器翻译等领域都有着广泛而重要的应用。 - Recently, natural language text watermarking has been the research focus in text watermarking field.
基于自然语言的文本水印是近年来文本水印研究的热点。 - The word relevant reflects correlative degree of words, and it is widely used in natural language processing, information retrieval, text classification and so on.
词语的相关性反映词语间的关联程度，它在自然语言处理、信息检索、文本分类等领域都有着广泛的应用。 - It uses the redundancy of the natural language content in text to hide secret information, for the main purpose of secure communications.
语言隐写术作为文本信息隐藏的一子类，使用文本中自然语言内容的冗余来隐藏信息，并以安全通信为主要目的。 - Moreover, these methods do not effectively solve natural language problems existed in text data.
而且，这类算法没有很好地解决文本数据中存在的自然语言问题：同义词和多义词。 - Therefore, we can know that the research object is unstructured tree text and the study goal is to extract knowledge, involving natural language processing, text mining and other related fields.
明确了研究对象是非结构化的自由文本，研究目标是从非结构化的自由文本中抽取知识，涉及了自然语言处理和文本挖掘等领域的相关技术。 - Furthermore, the performances of tasks in Natural language Processing field, such as text classification and information retrieval could be promoted with high quality labels.
而且，好的标签对于提高文本分类、信息检索等自然语言处理任务的性能也具有极大的帮助。 - Synonyms and polysemy problems are unique phenomena to natural language text data.
近义词和多义词问题也是文本数据特有的自然语言现象。 - However, owing to the unique language features of short text, processing technique of short text differs from that of the natural language in traditional text.
短消息文本自身的语言特点决定了它在自然语言处理中的处理技术与普通长文本有所不同。 - The main purpose of information extraction is to transform unstructured natural language text into semi-structured or structured data, easy for people to obtain key information quickly and accurately.
信息抽取的主要目的是将非结构化的自然语言文本转化成半结构化或结构化的数据，方便人们准确、快速地获取关键信息。 - The key of the work is natural language text understanding.
工作的中心是自然语言篇章理解。 - It is noteworthy that this psychological reality of dependency grammar may explain why it is a comparatively suitable means for natural language processing tasks such as authentic text processing in corpus and machine translation, etc.
值得指出的是，也许正是它所具有的心理现实性，使它能够得以成功地应用于语料库的真实文本处理和机器翻译等自然语言处理的任务中。