基于遗传算法的网络资源数据挖掘技术

Data Mining Technology of Network Resources Based on Genetic Algorithm

为了提高数据挖掘的水平,避免挖掘成果中存在噪声信息对技术应用造成影响,本文引进遗传算法,设计了一种针对网络资源的全新数据挖掘技术。通过算法对目标资源数组的迭代,锁定目标密集区域,确定网络资源数据挖掘方向;根据不同网络资源类型设定数据挖掘规则,提取规则与多个数据挖掘行为端口进行对接;在输出网络资源挖掘子集结果后,进行数据的清洗与筛查删除数组中的冗余值,优化数据挖掘效果。实验证明,该挖掘技术不仅可以实现对网络资源的深度挖掘,还可以保证挖掘后的结果具有较强的连续性,在一定程度上解决挖掘结果存在噪声的问题。

In order to improve the level of data mining and avoid the impact of noise information in mining results on technology application, this paper introduces genetic algorithm and designs a new data mining technology for network resources. Through the iteration of the target resource array, the target dense area is locked, and the direction of network resource data mining is determined;According to different network resource types, set data mining rules, extract rules and connect with multiple data mining behavior ports;After outputting the subset results of network resource mining, clean and screen the data, delete the redundant values in the array, and optimize the effect of data mining. Experiments show that this mining technology can not only realize the deep mining of network resources, but also ensure the strong continuity of the mining results, and solve the problem of noise in the mining results to a certain extent.