Recent years have witnessed a surge in social networking as a popular medium for establishing online communications and relationships. My research in this area ranges from structural analysis of large graphs to developing value-centric social networking and situational applications, exploiting converged networks and Web 2.0 principles. I am currently investigating activity-oriented social networking, addressing challenges that exist in exploiting user context to engage them through a social networking medium. Following is a brief of some of the activities:
R-U-In?: A Platform for Real-time Activity management using Social Networks and Presence
R-U-In? (pronounced Are You In?) is a social networking platform that leverages Web 2.0 and Converged Networks technologies to create
a rich next-generation service. R-U-In? allows a user to search (in real-time) and solicit participation of like-minded
partners for an activity of mutual interest (e.g. a rock concert, a soccer game, or a movie) through multi-modal communication
tools (IM,SMS,Web). It exploits content and capabilities of a converged telecom/IP infrastructure, blended together with Web 2.0
technologies, to provide an enhanced, value-added service experience.
R-U-In? draws upon the strengths of Web 2.0 and converged networks technologies to create an upto-date contextual information store about participants and
their interests, and subsequently applies contextual modeling and reasoning techniques to enable “social search” on this platform. R-U-In? is a step in the direction of
truly ubiquitous social networking – that does not require a user go to a web site to be social, but one that seamlessly integrates with the “social” context in our personalities, our
communications, and our activities.
Representative Publication
N. Banerjee, D. Chakraborty, K. Dasgupta, S. Mittal, S. Nagar, Saguna, R-U-In? - Exploiting Rich Presence and Converged Communications for Next-generation
Activity-Oriented Social Networking. In Proc. 10th International Conference on Mobile Data Management (MDM), May, 2009.
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Snazzy: Social Network analysis for Telecom Business Intelligence
With ever growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives
to their customers. In this project, we investigated structural properties of large telecom call graphs to extract meaningful and non-trivial knowledge about
customers. The project has applicability in several business verticals ranging from campaign management, mobile advertising, churn prediction. More information on this
project is available here.
Representative Publication
A. Nanavati, R. Singh, D. Chakraborty, K. Dasgupta, S. Mukherjea, G. Das, S. Gurumurthy, A. Joshi, Analyzing the Structure and Evolution of Massive Telecom Graphs,
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2008.