Research related to FACTORIE is described in several publications. These include:
- Andrew McCallum, Karl Schultz, Sameer Singh. "FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs". In Advances on Neural Information Processing Systems (NIPS), 2009.
- Sameer Singh, Karl Schultz, Andrew McCallum. "Bi-directional Joint Inference for Entity Resolution and Segmentation using Imperatively-Defined Factor Graphs". In Machine Learning and Knowledge Discovery in Databases (Lecture Notes in Computer Science) and European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2009.
- Andrew McCallum, Khashayar Rohanemanesh, Michael Wick, Karl Schultz, Sameer Singh. "[FACTORIE: Efficient Probabilistic Programming for Relational Factor Graphs via Imperative Declarations of Structure, Inference and Learning]"(http://www.cs.umass.edu/~mccallum/papers/factorie-nipsws.pdf). In Advances on Neural Information Processing Systems, Workshop on Probabilistic Programming, 2008.
- Michael Wick, Andrew McCallum, Gerome Miklau. "[Scalable Probabilistic Databases with Factor Graphs and MCMC"(http://www.cs.umass.edu/~mwick/MikeWeb/Publications_files/wick10scalable.pdf). International Conference on Very Large Data Bases (VLDB), 2010.
- Michael Wick, Khashayar Rohanemanesh, Aron Culotta, Andrew McCallum. "SampleRank: Learning Preferences from Atomic Gradients". In Advances on Neural Information Processing Systems, Workshop on Advances in Ranking, 2009.
If you know of a paper that uses Factorie but is not mentioned here, let us know.