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Personal Information

Name: Nitin Agarwal

Homepage: (Never completed and hasn't been updated in a while)

Student: 2nd Year Master Student at LTI

Other Information

I am crediting the course. I hope to learn in general how interaction in social networks can be understood by mining text data corresponding to the interaction. Other phenomena like evolution of a social network over time etc. which might manifest itself in form of text are also of deep interest to me.

For my research I have been working mainly on probabilistic models of text especially in the genre of scientific articles. I have decent understanding of latent Bayesian models. I have been working on a summarization system for scientific articles. I have been using latent models such as LDA and variants of the model and other clustering techniques to assist in discovery of common themes across scientific articles.

I have some ideas about a potential project which are in the form of a rough draft at this link [1]. I propose a graphical model for modeling topics conditioned on relation between the authors in a networked set of scientific articles (such as Citeseer or ACL anthology). At this point I am really not sure if its viable amount of work for a course project, so I would be discussing that with my project team mates to come up with more attainable objectives.

Wikified topic paper (Home work 2)

Wikified topic paper (Home work 3)