新闻网页分类使用url内容和结构属性

2016 2nd International Conference on Next Generation Computing Technologies (NGCT) Pub Date : 2016-10-01 DOI:10.1109/NGCT.2016.7877434

Chandrakala Arya, S. Dwivedi

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引用次数: 12

摘要

这项工作的动机源于从印度新闻网站语料库中检索有用的网络新闻页面的需要。新闻网页与其他网页的对比;准确识别网络新闻，对网络新闻进行准确分类是至关重要的。我们可能会找到一种简单而有效的技术来从网络语料库中挖掘新闻文章。为了完成这一任务，新闻网页分类的自动识别方法被推荐使用基于内容、结构和统一资源定位符(URL)属性组合的分类规则。我们收集了来自10个不同新闻网站的新闻文档。我们使用Naïve贝叶斯算法来区分新闻文章和非新闻文章，例如广告，而不是相关链接。

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News web page classification using url content and structure attributes

The incentive for this work originates from the need of retrieving useful web news pages from the Indian news websites corpus. News web pages contrast from other web pages; it is mainly vital to recognize web news accurately for precise classification. We will likely locate a simple yet efficient technique to mine news articles from web corpus. To accomplish this task, the automatic recognition method has been recommended for news web page classification that uses classification rules based on a combination of content, structure and uniform resource locator (URL) attributes. We gathered news web documents from 10 different news websites. We use Naïve Bayes algorithm to distinguish news articles from non-news articles examples advertisements, not related links.

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来源期刊

2016 2nd International Conference on Next Generation Computing Technologies (NGCT)

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