Researches and papers using FlexCRFs or PCRFs for conducting experiments should include the following citation:

Xuan-Hieu Phan, Le-Minh Nguyen, and Cam-Tu Nguyen. FlexCRFs: Flexible Conditional Random Fields, 2004.

Here is an incomplete list of published papers that use and cite FlexCRFs or PCRFs:

  1. X. Wang, X. Liu, Z. Shi, and H. Sui. A feature binding computational model for multi-class object categorization and recognition. Neural Computing and Applications, 2011.
  2. X. Duan, M. Zhang, and H. Li. Pseudo-word for phrase-based machine translation. In Proc. of ACL, 2010.
  3. F. Liu and Y. Liu. Identification of Soundbite and Its Speaker Name Using Transcripts of Broadcast News Speech, The ACM Transactions on Asian Language Information Processing (ACM TALIP), Vol.9, No.1, 2010.
  4. L. Badino. Identifying Prosodic Prominence Patterns for English Text-to-Speech Synthesis. PhD Thesis, University of Edinburgh, 2010.
  5. F. Zhao, J. Peng, J. Debartolo, K. Freed, T. Sosnick, and J. Xu. A probabilistic and continuous model of protein conformational space for template-free modeling. Journal of Computational Biology, Vol.17, No.6, 2010.
  6. X. Geng, J. Guan, Q. Dong, and S. Zhou. Protein backbone dihedral angle prediction based on probabilistic models. In Proc. of Bioinformatics and Biomedical Engineering (iCBBE), 2010.
  7. B. Liu, X. Wang, L. Lin, B. Tang, Q. Dong, and X. Wang. Prediction of protein binding sites in protein structures using hidden Markov support vector machine. BMC Bioinformatics, 2009.
  8. Q. Dong, S. Zhou, J. Guan. Improving prediction of the contact numbers of residues in proteins from primary sequences. IJCBS '09 Proceedings of the 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, 2009.
  9. F. Maes, L. Denoyer, and P. Gallinari. Structured prediction with reinforcement learning. Machine Learning Journal, Vol.77, No.2-3, 2009.
  10. F. Zhao, J. Peng, J. Debartolo, K. Freed, T. Sosnick, and J. Xu. A probabilistic graphical model for ab initio folding. Research in Computational Molecular Biology, 2009.
  11. T. Buzhou, W. Xuan, and W. Xiaolong. Protein secondary structure prediction using large margin methods. The 8th IEEE/ACIS International Conference on Computer and Information Science (ICIS), 2009.
  12. K. Hirohata, N. Okazaki, S. Ananiadou, and M. Ishizuka. Identifying sections in scientific abstracts using conditional random fields. In Proc. of the IJCNLP, 2008.
  13. J. Zhang, C. Zong, and S. Li. Sentence type based reordering model for statistical machine translation. In Proc. of COLING, 2008.
  14. J. Zhao, K. Liu, and G. Wang. Adding redundant features for CRFs-based sentence sentiment classification. In Proc. of EMNLP, 2008.
  15. C. Xu, Y.-F. Zhang, G. Zhu, Y. Rui, H. Liu, and Q. Huang. Using webcast text for semantic event detection in broadcast sports video. IEEE Transactions on Multimedia, Vol.10, No.7, 2008.
  16. L. Li, X. Wang, Y. Yu, X. Wang. Model fusion of conditional random fields. In Proc. of IEEE International Conference on System, Man, and Cybernetics, 2007.
  17. F. Maes, L. Denoyer, and P. Gallinari. Sequence labeling with reinforcement learning and ranking algorithms. In Proc. of ECML, 2007.
  18. G. Wisniewski and P. Gallinari. From Layout to Semantic: A reranking model for mapping Web documents to mediated XML representations. In Proc. of the 8th Conference on Large-scale Semantic Access to Content (Text, Image, Video, and Sound), RIAO, 2007.
  19. P. Lu, Y. Yang, Y. Gao, and H. Ren. Hierarchical Conditional Random Fields (HCRF) for Chinese Named Entity Tagging. In Proc. of The Third International Conference on Natural Computation, 2007.
  20. G. Wisniewski and P. Gallinari. Relaxation labeling for selecting and exploiting efficiently non-local dependencies in sequence labeling. In Proc. of the European Conference on Principles of Data Mining and Knowledge Discovery (PKDD), 2007.
  21. J. Yuan, J. Li, and B. Zhang. Gradual transition detection with conditional random fields. In Proc. of the 15th International Conference on Multimedia, 2007.
  22. W. Li, D. Qian, Q. Lu, and C. Yuan. Detecting, categorizing and clustering entity mentions in Chinese text. In Proc. of the 30th ACM SIGIR, 2007.
  23. M.-H. Li, L. Lin, X.-L. Wang, and T. Lin. Protein-protein interaction site prediction based on conditional random fields. Bioinformatics, 23(5):597-604, 2007.
  24. T. Wang, J. Li, Q. Diao, W. Hu, Y. Zhang, and C. Dulong. Semantic event detection using conditional random fields. In Proc. of the 2006 Conf. on Computer Vision and Pattern Recognition Workshop, 2006.
  25. J. Shan, Y. Chen, Q. Diao, Y. Zhang. Parallel information extraction on shared memory multi-processor system. In Proc. of International Conference on Parallel Processing, 2006.
  26. D.-H. Tran, T.-H. Pham, K. Satou, T.-B. Ho. Conditional random fields for predicting and analyzing histone occupancy, acetylation and methylation areas in DNA sequences. In Proc. of the EvoWorkshops, 2006.
  27. C.-T. Nguyen, T.-K. Nguyen, X.-H. Phan, L.-M. Nguyen, and Q.-T. Ha. Vietnamese word segmentation with CRFs and SVMs: an investigation. In Proc. of the 20th Pacific Asia Conference on Language, Information, and Computation, 2006.
  28. X.-H. Phan, L.-M. Nguyen, Y. Inoguchi, T.-B. Ho, and S. Horiguchi. Improving discriminative sequential learning by discovering important associations of statistics. ACM Transactions on Asian Language and Information Processing, 5(4):413-438, 2006.
  29. Y.-H. Lee, M.-Y. Kim, and J.-H. Lee. Chunking using conditional random fields in Korean texts. In Proc. of IJCNLP, 2005.
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