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

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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Ing is a vital and practical information processing task in natural language processing, and becomes an important problem in domains such as Internet information retrieval.

自动文摘研究作为自然语言处理研究的一个重要且实用的分支，目前逐渐成为Internet信息检索等应用领域的重要研究课题之一。

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The Relationship Modeling Engine uses natural language processing and sophisticated semantic analysis techniques to analyze and categorize text.

Relationship Modeling Engine使用自然语言处理和高级的语义分析技术对文本进行分析和分类。

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Based on these experimental results, the disadvantages and merits of small computing features, like skin color, edge and so on, are analyzed.

通过大量的试验结果，分析了选取肤色信息、边缘信息等小计算量特征用于人脸检测的局限和意义。

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In view of the inherent shortcomings of edge-directed interpolation algorithm and locally-adaptive zooming algorithm, a new algorithm is proposed.

针对边缘方向插值算法计算量大、边界的处理效果不理想，而自适应放大算法对权值因子的选择太过简单的问题，提出了一种新算法。

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