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首页> 外文期刊>International journal of computer science and network security >Improved PageRank algorithm using structural web mining techniques and bee colony algorithm
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Improved PageRank algorithm using structural web mining techniques and bee colony algorithm

机译:使用结构化网络挖掘技术和蜂群算法的改进的PageRank算法

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摘要

The current explosion of information has made use of search engines inevitable. Search engines are also trying to provide better responses to users. In this paper, an extended version of PageRank algorithm will be presented. In the proposed version, first the pre-processing operation is performed on the log file that includes data cleaning, separation of users and identification of sessions. To delete inappropriate inputs from the log file, data clearing will be used. Time-based methods were used to identify sessions and consider the pages as a session. Interests of users in pages are derived based on two criteria: page visiting frequency and duration of stay on page. Then, inspired by the bee colony algorithm, accuracy was improved. The results indicate that the proposed method has less errors compared to rival methods.
机译:当前的信息爆炸已经不可避免地使用搜索引擎。搜索引擎还试图为用户提供更好的响应。在本文中,将提出PageRank算法的扩展版本。在建议的版本中,首先对日志文件执行预处理操作,包括数据清理,用户分离和会话标识。要从日志文件中删除不适当的输入,将使用数据清除。基于时间的方法用于标识会话,并将页面视为会话。用户对页面的兴趣是基于两个标准得出的:页面访问频率和页面停留时间。然后,受蜂群算法启发,提高了准确性。结果表明,与竞争对手的方法相比,该方法具有更少的误差。

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