[1]LIANG Lu,WANG Biao,WANG Jianhui,et al.Analysis of telecom customer churn based on fine-grained association rule mining[J].CAAI Transactions on Intelligent Systems,2015,10(3):407-413.[doi:10.3969/j.issn.1673-4785.201404050]
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Analysis of telecom customer churn based on fine-grained association rule mining

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 3 Page number: 407-413 Column: 学术论文—机器学习 Public date: 2015-06-25
Title:
Analysis of telecom customer churn based on fine-grained association rule mining
Author(s):
LIANG Lu;  WANG Biao;  WANG Jianhui;  LIU Dongning
Faculty of Computer Science, Guangdong University of Technology, Guangzhou 510006, China
Keywords:
telecom customer churn; fine grain; association rules; logic method; one clause at a time (OCAT); heuristic rules
CLC:
TP182
DOI:
10.3969/j.issn.1673-4785.201404050
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 experiment we adopt the one clause at a time (OCAT) algorithm on association rule mining for speeding up the convergence 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.
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