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Searching, Translating and Classifying Information in Cyberspace

机译:在网络空间中搜索,翻译和分类信息

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In this paper we describe current search technologies available on the web, explain underlying difficulties and show their limits, related to either current technologies or to the intrinsic properties of all natural languages. We then analyze the effectiveness of freely available machine translation services and demonstrate that under certain conditions these translation systems can operate at the same performance levels as manual translators. Searching for factual information with commercial search engines also allows the retrieval of facts, user comments and opinions on target items. In the third part we explain how the principle machine learning strategies are able to classify short passages of text extracted from the blogosphere as factual or opinionated and then classify their polarity (positive, negative or mixed).
机译:在本文中,我们描述了当前在网络上可用的搜索技术,解释了潜在的困难并显示了与当前技术或所有自然语言的固有属性相关的限制。然后,我们分析了免费提供的机器翻译服务的有效性,并证明了在某些条件下,这些翻译系统可以以与手动翻译器相同的性能水平运行。使用商业搜索引擎搜索事实信息还可以检索事实,用户评论和目标项目的观点。在第三部分中,我们解释了机器学习原理的原理如何能够将从Blog圈中提取的短文本分类为事实或观点,然后将其极性分类(正,负或混合)。

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