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1)  Web Content collection
Web文本采集
2)  Web text
Web文本
1.
Research of Web Text Mining Technology Based on Hidden Markov Model;
基于隐马尔可夫模型的Web文本挖掘技术研究
2.
Based on the analysis about the characters of Web text information, this paper has discovered the essential technology, such as the goal sample characteristic withdraws, participle processing and the Web text classification.
本文在分析Web文本信息特征的基础上,揭示了Web文本数据挖掘的目标样本的特征提取、分词处理与Web文本分类等关键技术,以Google为例讨论了该技术在网络信息检索中的应用。
3.
With a brief summary and analysis of the present research and experiment on Web text feature extraction, this paper compares the advantages and shortages of each method, points out the difficulties and problems in the research, and based on this, forecasts the future development and tendency of the research in this domain.
本文对当前有关Web文本特征提取方法的研究和试验进行了简要的综述和分析,比较了每类方法的优势和不足,指出研究中存在的难点和共同探讨的问题,并在此基础上,对该领域未来研究的发展方向和趋势进行了预测。
3)  Web documents
Web文本
1.
In this paper,based on the analyses of features of Web documents,this paper does research the approach of classification in Vector Space Model and select of Kernel function.
Web文本分类技术是数据挖掘中一个研究热点领域,而支持向量机又是一种高效的分类识别方法,在解决高维模式识别问题中表现出许多特有的优势。
2.
Based on the analyses of traditional Nearest Neighbor text categorization and features of Web documents, a new method is put forward to effectively organize the rich information on the Internet.
为了更有效的组织Internet上丰富的信息资源,通过分析传统的近邻文本分类方法技术以及Web文本的特点,提出了一种新的简单有效的网页分类方法。
3.
In this paper, based on the analyses of features of Web documents, this paper does research the approach of classification in Vector Space Model and select of Kernel function.
Web文本分类技术是数据挖掘中一个研究热点领域,而支持向量机又是一种高效的分类识别方法,在解决高维模式识别问题中表现出许多特有的优势。
4)  Web-based Data-Collection
Web数据采集
5)  Web crawling
Web信息采集
1.
During the course of Web crawling, it is needed to judge if the coming URLs are in the collection of crawled pages.
在Web信息采集的过程中,需要判断待采页面是否在已采页面集合中。
2.
The paper introduces the design of customized Web crawling system Psearch, analyses the acquirement of user s personalized interests, the selection of the order in which a crawler should visit the URLs it has seen and the evaluation of similarity between retrieved pages and user s interests in detail.
本文介绍了个性化Web信息采集系统PSearch的设计,重点分析了Psearch中用户兴趣个性化信息的获取、待采页面的选择和相关度的判定。
3.
With the explosion of Web information, the performance of Web crawling has become a big challenge.
随着Web信息的爆炸性增长,对Web信息采集的性能提出了巨大的挑战。
6)  Chinese Web texts
中文Web文本
1.
This paper deals with Chinese Web texts categorization techniques.
最后通过实验测试了使用KNN算法的中文Web文本分类技术的效果。
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