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On the structural properties of massive telecom call graphs: findings and implications
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Source Conference on Information and Knowledge Management archive
Proceedings of the 15th ACM international conference on Information and knowledge management table of contents
Arlington, Virginia, USA
SESSION: Graphs and trees table of contents
Pages: 435 - 444  
Year of Publication: 2006
ISBN:1-59593-433-2
Authors
Amit A. Nanavati  IBM India Research Laboratory, New Delhi, India
Siva Gurumurthy  IBM India Research Laboratory, New Delhi, India
Gautam Das  IBM India Research Laboratory, New Delhi, India
Dipanjan Chakraborty  IBM India Research Laboratory, New Delhi, India
Koustuv Dasgupta  IBM India Research Laboratory, New Delhi, India
Sougata Mukherjea  IBM India Research Laboratory, New Delhi, India
Anupam Joshi  University of Maryland, Baltimore County, Maryland
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
Publisher
ACM  New York, NY, USA
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ABSTRACT

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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Amit A. Nanavati: colleagues
Siva Gurumurthy: colleagues
Gautam Das: colleagues
Dipanjan Chakraborty: colleagues
Koustuv Dasgupta: colleagues
Sougata Mukherjea: colleagues
Anupam Joshi: colleagues