基于加权随机森林的Web数据库检索结果智能分类方法  

Intelligent classification method of Web database search results based on a weighted random forest

作　　者：马秀梅 Ma Xiumei(Institute of Technology,Lanzhou Modern Vocational College,Lanzhou 730300,China)

机构地区：[1]兰州现代职业学院理工学院,兰州730300

出　　处：《现代计算机》2024年第16期25-29,共5页Modern Computer

摘　　要：Web数据库检索结果具有数据复杂、数量庞大的特点,数据间的复杂关系处于一种模糊状态,导致隶属度区别较小,分类过程需要多次迭代,效率较低。因此,提出了基于加权随机森林的Web数据库检索结果智能分类方法。提取Web数据库检索结果数据特征,并对Web数据库检索结果进行冗余处理。经过冗余处理之后,采用加权随机森林技术确定Web数据库检索结果模糊隶属度的范围。最后通过计算样本的分类权值,设计Web数据库检索结果分类器,实现Web数据库检索结果智能分类。实验结果表明:该方法的F1值均在95%以上,最长分类时间仅为7.8 s,表明本文方法能够更快速、精确地完成分类任务。The search results of Web database have the phenomenon of complex data and a large number of data.The complex relationships between data are in a fuzzy state,resulting in a small difference in membership,and the classification process requires many iterations and low efficiency.Therefore,the intelligent classification method of Web database retrieval results based on the weighted random forest is proposed.Data features of the Web database search results were extracted and the Web database search results were processed redundantly.After redundancy processing,the weighted random forest technique was used to determine the range of fuzzy membership of Web database search results.Finally,by calculating the classification weights of samples,a Web database search result classifier is designed to realize the intelligent classification of Web database search results.The experimental results show that the F1 value of this method is above 95%,and the longest classification time is only 7.8 s,indicating that the method can complete the classification task more quickly and accurately.

关 键 词：加权随机森林 WEB数据库 模糊隶属度 智能分类方法 

分 类 号：TP393.09[自动化与计算机技术—计算机应用技术] TP181[自动化与计算机技术—计算机科学与技术]