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Nachiketa Sahoo is an assistant professor in the Information Systems Department at the School of Management, Boston University. His broad area of research is Machine Learning in Information Systems research (Research Statement). Currently he is working on these specific topics
Contact Information595 commonwealth ave, office 627 |
‘‘The Halo Effect in Multi-component Ratings and its Implications for Recommender Systems: The Case of Yahoo! Movies’’, Information Systems Research, 2012, N. Sahoo, R. Krishnan, G. Duncan, J. Callan
‘‘A Hidden Markov Model for Collaborative Filtering’’, MIS Quarterly forthcoming, N. Sahoo, P. Singh, T. Mukhopadhyay
‘‘Seeking Variety: A Dynamic Model of Employee Blog Reading Behavior’’, P. Singh, N. Sahoo, T. Mukhopadhyay
‘‘Incentivizing Enterprise Social Media Participation under Employee Heterogeneity’’, P. Singh, N. Sahoo, T. Mukhopadhyay
‘‘Socio-temporal analysis of conversations in intra-organizational blogs’’, N. Sahoo, R. Krishnan, C. Faloutsos
‘‘A Hidden Markov Model for Collaborative Filtering’’, The 2011 Winter Conference on Business Intelligence, N. Sahoo, P. Singh, T. Mukhopadhyay
‘‘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
‘‘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
‘‘An Approach to Multi-objective Facility Layout Planning.’’ Industrial Engineering Journal, 2002, XXXI No. 4, 20–25, N. Sahoo, T. Shekhar, S. Sahu
‘‘Artist Ranking through Analysis of Online Community Comments’’, IBM Research Technical Report, J. Grace, D. Gruhl, K. Haas, M. Nagarajan, C. Robson, N. Sahoo
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)
‘‘Efficient Random-Walk-with-Restart Computation using Dynamic Partitioning of Large Sparse Graphs’’, R. Sabhnani, N. Sahoo, A. Shanbhag
Designing Systems and Data Management (IS883) Fall ’11
Managing Data Resources (IS465) Fall ’11
Management Information Systems (70-451) Fall ’09, Spring ’10, Fall ’10
A short CV (PDF).