智能系统学报Issue(3)：407-413,7.DOI:10.3969/j.issn.1673-4785.201404050
基于细精度关联规则挖掘的电信客户流失分析
Analysis of telecom customer churn based on fine-grained association rule mining
摘要
Abstract
When using traditional association rule mining such as decision tree to analyze the problem of telecom customer churn, we always meet the problem that the dependency of attributes are not enough fine, which means traditional methods not only cannot analyze the internal structure and hidden fine⁃grained related rules of attributes, but also cannot satisfy the needs of analyzing massive telecom data. In this paper, we solve the above problems by using fine⁃grained association rule mining. We firstly design a binary coding method from logic viewpoint to break attributes to segments, and then build the positive and negative training sample sets based on segments. In experi⁃ment we adopt the one clause at a time ( OCAT) algorithm on association rule mining for speeding up the conver⁃gence speed and saving the overhead of time and memory. Finally, the experimental result shows that this method improves the fine⁃grained of the association rule, which can be easily used in parallel computing to raise efficiency, and satisfy the requirements of current telecom application.关键词
电信客户流失/细精度/关联规则/逻辑方法/OCAT/启发式规则Key words
telecom customer churn/fine grain/association rules/logic method/one clause at a time ( OCAT)/heuristic rules分类
信息技术与安全科学引用本文复制引用
梁路,王彪,王剑辉,刘冬宁..基于细精度关联规则挖掘的电信客户流失分析[J].智能系统学报,2015,(3):407-413,7.基金项目
国家“863”计划重大项目（2013AA01A212）；国家自然科学基金资助项目（61272067，61104156）；广东省自然科学基金资助项目（9451009001002777）． （）
