@inproceedings{edd4428960844f698989f4f0f5ff6b1f,
title = "K-means based clustering on mobile usage for social network analysis purpose",
abstract = "The development of mobile network technology provides a great potential for social networking services. This paper studied data mining for social network analysis purpose, which aims at find people's social network patterns by analyzing the information about their mobile phone usage. In this research, the real database of MIT's Reality Mining project is employed. The classification model presented in this project provides a new approach to find the proximity between users - based on their registration frequencies to specific cellular towers associated their working places. K-means Algorithm is applied for clustering, and we find the result could achieve the highest accuracy 0.823 at the number groups k = 6. The clustering result successfully reflects the higher proximity (at work) for the intraclass subjects.",
keywords = "Clustering, Data mining, K-Means, Social network analysis",
author = "Xu Yang and Yapeng Wang and Dan Wu and Athen Ma",
year = "2010",
language = "English",
isbn = "9788988678312",
series = "Proc. - 6th Intl. Conference on Advanced Information Management and Service, IMS2010, with ICMIA2010 - 2nd International Conference on Data Mining and Intelligent Information Technology Applications",
pages = "223--228",
booktitle = "Proc. - 6th Intl. Conference on Advanced Information Management and Service, IMS2010, with ICMIA2010 - 2nd International Conference on Data Mining and Intelligent Information Technology Applications",
note = "6th International Conference on Advanced Information Management and Service, IMS2010, with 2nd International Conference on Data Mining and Intelligent Information Technology Applications, ICMIA2010 ; Conference date: 30-11-2010 Through 02-12-2010",
}