The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Trawling the Web for emerging cyber-communities
WWW '99 Proceedings of the eighth international conference on World Wide Web
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
On maximum clique problems in very large graphs
External memory algorithms
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
ANF: a fast and scalable tool for data mining in massive graphs
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Structure and evolution of blogspace
Communications of the ACM - The Blogosphere
A novel evolutionary data mining algorithm with applications to churn prediction
IEEE Transactions on Evolutionary Computation
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Spectral clustering in telephone call graphs
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
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
Mobile call graphs: beyond power-law and lognormal distributions
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Spectral Clustering in Social Networks
Advances in Web Mining and Web Usage Analysis
Why We Twitter: An Analysis of a Microblogging Community
Advances in Web Mining and Web Usage Analysis
Group CRM: a new telecom CRM framework from social network perspective
Proceedings of the 1st ACM international workshop on Complex networks meet information & knowledge management
DisTec: Towards a Distributed System for Telecom Computing
CloudCom '09 Proceedings of the 1st International Conference on Cloud Computing
Achieving peer-to-peer telecommunication services through social hashing
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Exploring temporal egocentric networks in mobile call graphs
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
In-depth behavior understanding and use: The behavior informatics approach
Information Sciences: an International Journal
Structure, tie persistence and event detection in large phone and SMS networks
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Surprising patterns for the call duration distribution of mobile phone users
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Role defining using behavior-based clustering in telecommunication network
Expert Systems with Applications: An International Journal
Multiple level views on the adherent cohesive subgraphs in massive temporal call graphs
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Generative models for rapid information propagation
Proceedings of the First Workshop on Social Media Analytics
Comparing clustering schemes at two levels of granularity for mobile call mining
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
User association analysis of locales on location based social networks
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Proceedings of the third international workshop on Cloud data management
EigenSpokes: surprising patterns and scalable community chipping in large graphs
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
User modeling for telecommunication applications: experiences and practical implications
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Crisp and soft clustering of mobile calls
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
Quantifying reciprocity in large weighted communication networks
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Detecting abnormal patterns in call graphs based on the aggregation of relevant vertex measures
ICDM'12 Proceedings of the 12th Industrial conference on Advances in Data Mining: applications and theoretical aspects
Are call detail records biased for sampling human mobility?
ACM SIGMOBILE Mobile Computing and Communications Review
The Activation of Core Social Networks in the Wake of the 22 July Oslo Bombing
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Mining frequent graph patterns with differential privacy
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient community detection with additive constrains on large networks
Knowledge-Based Systems
Streaming algorithms for k-core decomposition
Proceedings of the VLDB Endowment
ACM SIGMOD Record
Hi-index | 0.00 |
With ever growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives to their customers. Toward this end, existing approaches have almost solely focussed on the individual behaviour of customers. Call graphs, that is, graphs induced by people calling each other, can allow telecom operators to better understand the interaction behaviour of their customers, and potentially provide major insights for designing effective incentives.In this paper, we use the Call Detail Records of a mobile operator from four geographically disparate regions to construct call graphs, and analyse their structural properties. Our findings provide business insights and help devise strategies for Mobile Telecom operators. Another goal of this paper is to identify the shape of such graphs. In order to do so, we extend the well-known reachability analysis approach with some of our own techniques to reveal the shape of such massive graphs. Based on our analysis, we introduce the Treasure-Hunt model to describe the shape of mobile call graphs. The proposed techniques are general enough for analysing any large graph. Finally, how well the proposed model captures the shape of other mobile call graphs needs to be the subject of future studies.