Nachiketa Sahoo's Homepage

Nachiketa Sahoo is a visiting assistant professor of Information Systems at the Tepper School of Business, Carnegie Mellon University. His broad area of research is Machine Learning in Information Systems research (Research Statement). Currently he is working on these two specific topics Personalized recommendation when user preferences are changing Targeted advertisement on online social networks Contact Information 5000 Forbes ave Tepper School of Business, 233A Posner Hall Pittsburgh, PA 15213 Email: reCAPTCHA, Ph: 412-268-2270

Journal Publications

• ‘‘The Halo Effect in Multi-component Ratings and its Implications for Recommender Systems: The Case of Yahoo! Movies’’, Information Systems Research–accepted, N. Sahoo, R. Krishnan, G. Duncan, J. Callan

Papers Under Review

• ‘‘A Hidden Markov Model for Collaborative Filtering’’, N. Sahoo, P. Singh, T. Mukhopadhyay

• ‘‘Seeking Variety: A Dynamic Model of Employee Blog Reading Behavior’’, P. Singh, N. Sahoo, T. Mukhopadhyay

Working Papers

• ‘‘Socio-temporal analysis of conversations in intra-organizational blogs’’, N. Sahoo, R. Krishnan, C. Faloutsos

Upcoming presentations

• ‘‘A Hidden Markov Model for Collaborative Filtering’’, The 2011 Winter Conference on Business Intelligence, N. Sahoo, P. Singh, T. Mukhopadhyay

Prior Conferences and Workshop Presentations

• ‘‘Expertise Discovery from Blogs by Tensor Factorization’’, Conference on Information Systems and Technology (CIST ’10), N. Sahoo, R. Krishnan

• ‘‘Seeking Variety: A Dynamic Model of Employee Blog Reading Behavior’’, Workshop on Information Systems Economics (WISE ’10), P. Singh, N. Sahoo, T. Mukhopadhyay

• ‘‘Modeling Blog Reading Dynamics’’, The Sixth Symposium on Statistical Challenges in Electronic Commerce Research (SCECR ’10), P. Singh, N. Sahoo, T. Mukhopadhyay

• ‘‘Modeling Blog Reading Dynamics’’, The 2010 Winter Conference on Business Intelligence, T. Mukhopadhyay, N. Sahoo, P. Singh

• ‘‘On analyzing multi-modal networks using Tensors’’, Workshop on Information in Networks (WIN’09), R. Krishnan, N.Sahoo

• ‘‘Socio-temporal analysis of conversation themes in blogs by tensor factorization’’, The Eighteenth Annual Workshop on Information Technologies and Systems (WITS’08), N. Sahoo, R. Krishnan

• ‘‘Link formation over intra-organizational blog network’’ Fourth Symposium on Statistical Challenges in Electronic Commerce Research (SCECR’08), N. Sahoo, R. Krishnan, J. Callan

• ‘‘Formation of Citation and Reply ties over intra-organizational blog network’’ Conference on Information Systems and Technology (CIST’08), N. Sahoo, R. Krishnan, J. Callan

• ‘‘Applications of Voting Theory to Information Mashups’’ In Proceedings of the second IEEE International Conference on Semantic Computing (ICSC’08), A. Alba, V. Bhagwan, J. Grace, D. Gruhl, K. Haas, M. Nagarajan, J. Pieper, C. Robson, N. Sahoo

• ‘‘Collaborative Filtering with Multi-component Rating for Recommender Systems.’’ In Proceedings of the Sixteenth Annual Workshop on Information Technologies and Systems (WITS’06), N. Sahoo, R. Krishnan, G. Duncan, J. Callan

• ‘‘Incremental Hierarchical Clustering of Text Documents.’’ In Proceedings of the Fifteenth ACM International Conference on Information and Knowledge Management (CIKM’06), N. Sahoo, J. Callan, R. Krishnan, G. Duncan, R. Padman

Invited Talks

• ‘‘Multi-component Rating and Collaborative Filtering for Recommender Systems’’, INFORMS Annual Meeting Data Mining Session, 2008, N. Sahoo, R. Krishnan, J. Callan

• ‘‘Filling in rating components that the users left out’’, INFORMS Annual Meeting Data Mining Session, 2007, N. Sahoo, R. Krishnan

Older Journal Publication

• ‘‘An Approach to Multi-objective Facility Layout Planning.’’ Industrial Engineering Journal, 2002, XXXI No. 4, 20–25, N. Sahoo, T. Shekhar, S. Sahu

Technical Report

• ‘‘Artist Ranking through Analysis of Online Community Comments’’, IBM Research Technical Report, J. Grace, D. Gruhl, K. Haas, M. Nagarajan, C. Robson, N. Sahoo

Reports and Theses

• Ph.D. thesis titled “Three Essays on Enterprise Information Systems Mining for Business Intelligence” at Heinz College, CMU.

• My second research paper at Heinz College is titled “Experiments with Multi-component Rating Collaborative Filtering for Improved Recommendation” (PDF)

• My MS project at Machine Learning Department at CMU is titled “Incremental Hierarchical Clustering of Text Documents” (PDF)

Other Unpublished Report

• ‘‘Efficient Random-Walk-with-Restart Computation using Dynamic Partitioning of Large Sparse Graphs’’, R. Sabhnani, N. Sahoo, A. Shanbhag

Teaching

• Management Information Systems (70-451) Fall ’09, Spring ’10, Fall ’10

Biographical Information

A short CV (PDF).