Optimising the mining strategy of web page based on ant colony algorithm of information entropy Online publication date: Fri, 08-Nov-2019
by Meiwen Guo; Jianping Peng; Yuanping Zhang; C.H. Chiu; Liang Wu
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 11, No. 4, 2019
Abstract: 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.
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