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Web Page Classification Using Distributed Learning Automata and Partitioning Graph Algorithm

机译:基于分布式学习自动机和分区图算法的网页分类

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The characteristic of dynamic websites is that they include hidden contents, and this huge repository is only accessible via the website interfaces. This is a vital capability of all search engines, thus providing the users with links that are more relevant and ranked according to their needs. The drawback of most search engine algorithms is that they rank pages based on hyperlinked relative importance to other pages, rather than user intent and interest. This paper proposes a method based on Learning Automata for the classification of the webpage searches.
机译:动态网站的特征是它们包含隐藏内容,并且只能通过网站界面访问此庞大的存储库。这是所有搜索引擎的一项至关重要的功能,因此可以为用户提供更相关的链接,并根据他们的需求对其进行排名。大多数搜索引擎算法的缺点是,它们基于对其他页面的超链接相对重要性而不是用户意图和兴趣来对页面进行排名。提出了一种基于学习自动机的网页搜索分类方法。

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