A methodology for workload characterization of E-commerce sites
Proceedings of the 1st ACM conference on Electronic commerce
ACM Transactions on Internet Technology (TOIT)
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
K-means clustering versus validation measures: a data distribution perspective
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
On the structural properties of massive telecom call graphs: findings and implications
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Spectral clustering with eigenvector selection
Pattern Recognition
Preferential behavior in online groups
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Social ties and their relevance to churn in mobile telecom networks
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Analyzing the Structure and Evolution of Massive Telecom Graphs
IEEE Transactions on Knowledge and Data Engineering
Influence and correlation in social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Feedback effects between similarity and social influence in online communities
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying user behavior in online social networks
Proceedings of the 1st Workshop on Social Network Systems
Large human communication networks: patterns and a utility-driven generator
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
TeleComVis: Exploring Temporal Communities in Telecom Networks
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Modelling and analysis of user behaviour in online communities
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Ontology paper: Community analysis through semantic rules and role composition derivation
Web Semantics: Science, Services and Agents on the World Wide Web
Discovering content-based behavioral roles in social networks
Decision Support Systems
Hi-index | 12.05 |
Understanding the individual behavior has shown to be of paramount importance to the triumph of the telecommunication operators to retain customers, enhance their purchasing capacity, and predict the churn rate. Different behavior patterns can be observed for different groups of users. Hence, there is an interesting problem posted in telecommunication network that how to define the users' role according to their behavior patterns. Traditionally, user behavior characterization methods generally based on their call detail record (CDR), which are user's individual features, are not appropriate to identify the role in network. In this paper, we develop a new methodology for identifying users' role based on their behaviors in telecommunication network using the social features instead of their individual features. Experiments have tested on synthetic data and large real datasets, and reveal good results on both of them. Finally, the methodology is not only limited to call graphs but also apply to other networks for role defining.