Learning to rank-based abnormal phone analysis in environment of telecommunication big data

Jian Liu; Ke Ji II; Runyuan Sun III; Kun Ma IV

doi:10.1117/12.2501789

26 July 2018 Learning to rank-based abnormal phone analysis in environment of telecommunication big data

Jian Liu, Ke Ji II, Runyuan Sun III, Kun Ma IV

Proceedings Volume 10828, Third International Workshop on Pattern Recognition; 108280M (2018) https://doi.org/10.1117/12.2501789
Event: Third International Workshop on Pattern Recognition, 2018, Jinan, China

Abstract

It is very important to find out abnormal calls and take effective control measures, but most of the current solutions are passive processing technology and lack active detection methods. Based on the existing telecom big data, through the statistical analysis of abnormal telephone behavior, the salient features which could represent the abnormal telephone were found. Then the the active detection method of abnormal telephone was designed based on the Ranking SVM sorting learning machine learning method. The experimental results on real datasets show that the proposed method can achieve higher accuracy under different sample sizes.

Citation Download Citation

Jian Liu, Ke Ji II, Runyuan Sun III, and Kun Ma IV "Learning to rank-based abnormal phone analysis in environment of telecommunication big data", Proc. SPIE 10828, Third International Workshop on Pattern Recognition, 108280M (26 July 2018); https://doi.org/10.1117/12.2501789

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