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首页> 外文期刊>International journal of reasoning-based intelligent systems >Optimising the mining strategy of web page based on ant colony algorithm of information entropy
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Optimising the mining strategy of web page based on ant colony algorithm of information entropy

机译:基于信息熵蚁群算法的网页挖掘策略优化

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摘要

The speed and quality for browsers to obtain page information are determined by the accuracy degree of web page information filtering. This research improved ant colony algorithm, introducing the information entropy with the ability to judge the probability of occurrence of information and adjusting its operation order. The study uses Sina homepage information from January 2017 to August as a sample, four indexes are used to evaluate the improved algorithm, which are maximum iterations, average execution time, average error rate and error percentage. It is found that the four indexes of improved algorithm have better effect on the precision of information mining than before, and the cost of this method has not increased significantly. This algorithm is used to provide web page information layout as well as information placement strategies, so as to help website operators and web page designers to further enhance the design and operation efficiency.
机译:浏览器获取页面信息的速度和质量取决于网页信息过滤的准确性。该研究改进了蚁群算法,引入了信息熵,具有判断信息出现概率和调整操作顺序的能力。该研究以2017年1月至8月的新浪首页信息为样本,使用四个指标评估改进算法,即最大迭代次数,平均执行时间,平均错误率和错误百分比。结果表明,改进算法的四个指标对信息挖掘的精度有较以往更好的效果,且该方法的成本并未显着增加。该算法用于提供网页信息的布局以及信息的放置策略,以帮助网站运营商和网页设计者进一步提高设计和运营效率。

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