沈阳工业大学学报2024，Vol.46Issue(3)：312-317,6.DOI:10.7688/j.issn.1000-1646.2024.03.11
基于决策树的社交网络隐式用户行为数据挖掘方法
Data mining method based on decision tree for implicit user behavior in social network
摘要
Abstract
In order to solve the problem of social network that it is difficult to calculate the association similarity in the process of data mining for implicit user behavior,a data mining method based on decision tree for implicit user behavior in social network was proposed.Social network was regarded as a vector space containing different dimensions,and users′ interest space and interest points on specific dimensions were calculated.After determining the sample attribute set,the test branch was established according to the known behavior data,and the attribute weight of branch subset was calculated.In addition,it was iterated until the data points with the same attributes were mined.Test results show that the as-proposed method can ensure accurate mining in the face of different types of implicit user behavior,and the search for target behavior data is effective and practical.关键词
决策树/社交网络/隐式用户行为/向量空间/属性集/数据挖掘/权重值/属性元素Key words
decision tree/social network/implicit user behavior/vector space/set of properties/data mining/weight value/attribute element分类
信息技术与安全科学引用本文复制引用
韩永印,王侠,王志晓..基于决策树的社交网络隐式用户行为数据挖掘方法[J].沈阳工业大学学报,2024,46(3):312-317,6.基金项目
国家自然科学基金面上项目(61876186) （61876186）
徐州市科技计划项目(KC21300). （KC21300）
