Processing NIL text requires unconventional linguistic knowledge and techniques. Developed to handle formal language text, the existing natural language processing methods exhibit less effectiveness in dealing with NIL text.

According to the principle of use of Web information extraction can be divided into six kinds of way. For example, information extraction of based on wrapper, information extraction based on HTML structure, information extraction based on natural language processing, and so on.

根据采用的原理可以将Web信息抽取分为六种方式，例如基于包装器语言的信息抽取、基于HTML结构的信息抽取、基于自然语言处理方式的信息抽取等等。

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This article discusses the standardization stage of information processing& information content, which human beings have reached. Information content standardization depends on the integration and development of Knowledge Base construction and XML/ RDF for natural language processing.

本文论述了人类信息处理已经达到信息内容的标准化阶段，信息内容的标准化有赖于自然语言处理中的知识库建设和可扩展标记语言（XML）、资源描述框架（RDF）的融合与发展。

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The experiment makes clear that choosing domain concept as character item is better than others. Its F1 of macro-average is 79.35%, and its F1 of micro-average is 88.00%.

实验表明，在自然语言处理中，选择领域概念作为特征项，其宏平均下的F1值为79.35%，微平均下的F1值为88.00%。

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Two methods for collecting the structured data are discussed, which are natural language processing ( NLP) and structured data entry ( SDE).

阐述了两种结构化数据采集的方法：自然语言处理（NLP）和结构化数据输入（SDE）。

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These types of systems include advanced natural language processing systems that can discover new terms and relationships by analyzing content ( such as document text in ECM systems).

这种系统包括高级的自然语言处理系统，它能够通过分析内容（比如ECM系统中的文档文本）发现新的词汇和关系。

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Lots of advanced AI techniques such as machine learning, knowledge representation, pattern identification, genetic algorithms and distributed intelligent systems have been applied to the research ofDSS.

许多先进的人工智能技术如机器学习、知识表示、自然语言处理、模式识别、遗传算法及分布式智能系统都被融入DSS的研究中。

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Co-Training, as an alternative to EM algorithm, is a well-known form of bootstrapping which is a topic of interest in NLP.

作为EM算法的替代，Co-Training是众所周知的自举算法，近来已经成为自然语言处理领域的兴趣焦点。

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Intelligent question answering system based on XML reasoned using repository, it is a combinative technique of AI, information searches and disposal of nature language and so on, it has many advantages such as intelligence, opening and etc.

基于XML的智能答疑系统利用知识库进行推理，是一个智能适应性的知识库系统，它是人工智能、信息检索和自然语言处理等技术的结合，具有智能性、开放性等优点。

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Search engine become the most commonly used information retrieval tool, it involves a database, information retrieval, artificial only, data mining, Java, natural language processing and other fields of theory and technology.

搜索引擎成为人们最常用的信息检索工具，它涉及数据库、信息检索、人工只能、数据挖掘、Java、自然语言处理等多个领域的理论和技术。

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In the field of natural language processing, entity recognition is the key technique in many Chinese information Processing applications such as information extraction, syntactic analysis, machine translation, metadata annotate for Semantic Web and so on.

在自然语言处理领域，实体识别是信息提取、句法分析、机器翻译、面向SEMANTIC WEB的元数据标注等应用领域重要的基础性工具。

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SGML and its application in natural language processing

标准通用置标语言SGML及其在自然语言处理中的应用

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ICM RME receives this message and processes it in two main phases: a multilingual Natural Language Processing ( NLP) phase, and a language-independent statistic Concept Modeling phase.

ICM RME接收这个消息并分两个主要阶段处理它：多语种的自然语言处理（Natural Language Processing，NLP）阶段，以及独立于语言的统计性的概念建模（Concept Modeling）阶段。

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Open domain question answering ( QA) represents a challenge of natural language processing, aiming at returning exact answers in response to natural language questions.

开放领域的问题回答（Question Answering）是自然语言处理领域中具有挑战性的研究方向。

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Web text mining deals with structure and unstructured data of the web to discover knowledge by use of data mining, machine learning, natural language processing, information retrieval, knowledge management.

Web文本挖掘采用数据挖掘、机器学习、自然语言处理、信息检索和知识管理等领域的技术来处理和分析非结构或半结构化的文本，从中提取有价值的知识。

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CIP aims to be a natural language processing suit of Chinese.

CIP目标是成为中文的自然语言处理套件。

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With the rapid growth of Internet and increase of electronic text, automatic text classification ( ATC) has been the hottest research issues in information retrieval and natural language processing.

随着Internet的迅猛发展和电子文档信息的不断丰富，文档自动分类日益成为信息检索和自然语言处理领域的研究热点。

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It is important to draw a distinction between natural language processing ( NLP) and specific n-gram grammars.

一定要对自然语言处理（NLP）和特定的n元语法加以区别。

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As a core issue of natural language processing ( NLP), high-performance syntactic analysis played an important role in NLP applications.

作为自然语言处理（Natural Language Processing，NLP）领域的一个核心问题，高性能句法分析在NLP应用领域中发挥了重要的作用。

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This article discusses Web-Based Open Domain Question Answering System and the relevant technologies, such as information retrieval, information extraction, natural language process and so on.

主要对基于Web的开放领域问答系统及其涉及的信息检索、信息抽取、自然语言处理等相关技术内容进行了分析研究。

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Document clustering is an important research topic of natural language processing and is widely applicable in areas such as information retrieval, web mining and digital libraries.

文本聚类是自然语言处理研究中一项重要研究课题，文本聚类技术广泛地应用于信息检索、Web挖掘和数字图书馆等领域。

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