TeleComVis: Exploring Temporal Communities in Telecom Networks
Abstract
By the structure of call graphs derived from huge amounts of Call Detail Records, we can find out the social communities in the call graphs and make different market strategies for these social communities in real telecom applications. However, traditional telecom business intelligence methods are short of ways to understand the social interactions. To fill this gap, we propose a Tele com Com munity Vis ual Analysis prototype tool, called TeleComVis , to analyze the call graphs derived from Call Detail Records. In the demo, we will show (1) the functions of TeleComVis ; (2) the critical techniques of finding statistically significant communities in real-world telecom applications. Using TeleComVis , users can both analyze the statistical properties of massive call graphs and explore the statistically significant communities and the temporal links interactively.
Cite
Text
Ye et al. "TeleComVis: Exploring Temporal Communities in Telecom Networks." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2009. doi:10.1007/978-3-642-04174-7_57Markdown
[Ye et al. "TeleComVis: Exploring Temporal Communities in Telecom Networks." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2009.](https://mlanthology.org/ecmlpkdd/2009/ye2009ecmlpkdd-telecomvis/) doi:10.1007/978-3-642-04174-7_57BibTeX
@inproceedings{ye2009ecmlpkdd-telecomvis,
title = {{TeleComVis: Exploring Temporal Communities in Telecom Networks}},
author = {Ye, Qi and Wu, Bin and Suo, Lijun and Zhu, Tian and Han, Chao and Wang, Bai},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2009},
pages = {755-758},
doi = {10.1007/978-3-642-04174-7_57},
url = {https://mlanthology.org/ecmlpkdd/2009/ye2009ecmlpkdd-telecomvis/}
}