摘要
随着互联网的快速发展,人们接收的外界信息越来越多,如何在海量信息中获取有价值的信息,是互联网领域需要解决的重点问题。数据挖掘算法是一门跨学科的综合技术,能够从海量信息中提取人们需要的有用数据。将数据挖掘算法应用在实际中,能够起到一定的应用效果,其涉及了一个非常重要的知识点--推荐系统。基于此,重点介绍Web下推荐系统数据挖掘算法的具体应用过程,结合关联规则和聚类算法,提高推荐系统的准确性。
With the rapid development of the Internet, people receive more and more external information. How to obtain valuable information from mass information is the key problem to be solved in the field of the Internet. Data mining algorithm is an interdisciplinary comprehensive technology, which can extract useful data from mass information. The application of data mining algorithm in practice can play a certain application effect, which involves a very important knowledge point - recommendation system. Based on this, this paper focuses on the specific application process of data mining algorithm of recommendation system on the Web, and combines association rules and clustering algorithm to improve the accuracy of recommendation system.
作者
彭文惠
吴小刚
Peng Wenhui;Wu Xiaogang(Yangjiang Polytechnic, Yangjiang Guangdong 529566, China;Beijing E-Hualu Information Technology Co., Ltd., Beijing 100043, China)
出处
《信息与电脑》
2019年第13期44-47,共4页
Information & Computer
关键词
WEB
推荐系统
数据挖掘
算法分析
Web
recommendation system
data mining
algorithmic analysis
