On the Structural Properties of Massive Telecom Graphs: Findings and Implications

Start: Friday, November 10, 2006, 01:00PM

End: Friday, November 10, 2006, 02:00PM

Location: 325b

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 talk, we use the Call Detail Records of a mobile operator from four geographically disparate regions to construct call graphs, and analyze 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.

Tags: graphs, graph analysis, link analysis

Host: Anupam Joshi


	UMBC eBiquity Events / Talks On the Structural Properties of Massive Telecom Graphs: Findings and Implications OWL metadata Update record		On the Structural Properties of Massive Telecom Graphs: Findings and Implications Tweet Speaker: Amit Anil Nanavati Start: Friday, November 10, 2006, 01:00PM End: Friday, November 10, 2006, 02:00PM Location: 325b 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 talk, we use the Call Detail Records of a mobile operator from four geographically disparate regions to construct call graphs, and analyze 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. Tags: graphs, graph analysis, link analysis Host: Anupam Joshi ,