Study on call detail records of family members based on classification model

DOI

10.2991/essaeme-16.2016.75How to use a DOI?

Keywords

Family Relation, calling patterns, machine learning, classifier models

Abstract

In telecommunication industry, machine learning techniques have been applied to the Call Detail Records (CDRs) for predicting customer behavior. To further investigate the information buried in huge amounts of CDRs, family relationship among mobile users can be identified, which helps the effective targeted marketing behavior, it is significantly important for increasing profitability. We use the information extracted from the CDRs analysis to identify customer calling patterns. then Customers calling patterns are given to a classification algorithm to generate a classifier model for predicting the family relation of a customer. We apply different machine learning techniques to build classifier models and compare them in terms of classification accuracy and computational performance. The reported test results demonstrate the applicability and effectiveness of the proposed approach.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Xingguo Wu
PY  - 2016/08
DA  - 2016/08
TI  - Study on call detail records of family members based on classification model
BT  - Proceedings of the 2016 International Conference on Economics, Social Science, Arts, Education and Management Engineering
PB  - Atlantis Press
SP  - 367
EP  - 371
SN  - 2352-5398
UR  - https://doi.org/10.2991/essaeme-16.2016.75
DO  - 10.2991/essaeme-16.2016.75
ID  - Wu2016/08
ER  -