Department of Computer Science

Machine Learning Research Group

University of Texas at Austin Artificial Intelligence Lab

Publications: 2004


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  1. Active Feature-Value Acquisition for Classifier Induction
    [Details] [PDF]
    Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond J. Mooney
    Technical Report UT-AI-TR-04-311, Artificial Intelligence Lab, University of Texas at Austin, February 2004.
  2. Active Feature-Value Acquisition for Classifier Induction
    [Details] [PDF]
    Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond J. Mooney
    In Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM-2004), 483-486, Brighton, UK, November 2004.
  3. A Probabilistic Framework for Semi-Supervised Clustering
    [Details] [PDF]
    Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney
    In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), 59-68, Seattle, WA, August 2004.
  4. Text Mining with Information Extraction
    [Details] [PDF]
    Un Yong Nahm
    PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, August 2004. 217 pages. Also appears as Technical Report UT-AI-TR-04-311.
  5. Collective Information Extraction with Relational Markov Networks
    [Details] [PDF]
    Razvan Bunescu and Raymond J. Mooney
    In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04), 439-446, Barcelona, Spain, July 2004.
  6. Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer
    [Details] [PDF]
    Gregory Kuhlmann, Peter Stone, Raymond J. Mooney, and Jude W. Shavlik
    In The AAAI-2004 Workshop on Supervisory Control of Learning and Adaptive Systems, July 2004.
  7. Using Soft-Matching Mined Rules to Improve Information Extraction
    [Details] [PDF]
    Un Yong Nahm and Raymond J. Mooney
    In Proceedings of the AAAI-2004 Workshop on Adaptive Text Extraction and Mining (ATEM-2004), 27-32, San Jose, CA, July 2004.
  8. Semi-supervised Clustering with Limited Background Knowledge
    [Details] [PDF]
    Sugato Basu
    In Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, 979--980, San Jose, CA, July 2004.
  9. Learnable Similarity Functions and Their Applications to Clustering and Record Linkage
    [Details] [PDF]
    Mikhail Bilenko
    In Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, 981--982, San Jose, CA, July 2004.
  10. Integrating Constraints and Metric Learning in Semi-Supervised Clustering
    [Details] [PDF]
    Mikhail Bilenko, Sugato Basu, and Raymond J. Mooney
    In Proceedings of 21st International Conference on Machine Learning (ICML-2004), 81-88, Banff, Canada, July 2004.
  11. Diverse Ensembles for Active Learning
    [Details] [PDF]
    Prem Melville and Raymond J. Mooney
    In Proceedings of 21st International Conference on Machine Learning (ICML-2004), 584-591, Banff, Canada, July 2004.
  12. Relational Markov Networks for Collective Information Extraction
    [Details] [PDF]
    Razvan Bunescu and Raymond J. Mooney
    In Proceedings of the ICML-04 Workshop on Statistical Relational Learning and its Connections to Other Fields, Banff, Alberta, July 2004.
  13. A Comparison of Inference Techniques for Semi-supervised Clustering with Hidden Markov Random Fields
    [Details] [PDF]
    Mikhail Bilenko and Sugato Basu
    In Proceedings of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL-2004), Banff, Canada, July 2004.
  14. Experiments on Ensembles with Missing and Noisy Data
    [Details] [PDF]
    Prem Melville, Nishit Shah, Lilyana Mihalkova, and Raymond J. Mooney
    In F. Roli, J. Kittler, and T. Windeatt, editors, {Lecture Notes in Computer Science:} Proceedings of the Fifth International Workshop on Multi Classifier Systems (MCS-2004), 293-302, Cagliari, Italy, June 2004. Springer Verlag.
  15. Explanation for Recommender Systems: Satisfaction vs. Promotion
    [Details] [PDF]
    Mustafa Bilgic
    Austin, TX, May 2004. Undergraduate Honor Thesis, Department of Computer Sciences, University of Texas at Austin.
  16. Active Semi-Supervision for Pairwise Constrained Clustering
    [Details] [PDF]
    Sugato Basu, Arindam Banerjee, and Raymond J. Mooney
    In Proceedings of the 2004 SIAM International Conference on Data Mining (SDM-04), April 2004.
  17. Learning Transformation Rules for Semantic Parsing
    [Details] [PDF]
    Rohit J. Kate, Yuk Wah Wong, Ruifang Ge, and Raymond J. Mooney
    April 2004. Unpublished Technical Report.
  18. Creating Diversity in Ensembles Using Artificial Data
    [Details] [PDF]
    Prem Melville and Raymond J. Mooney
    Journal of Information Fusion: Special Issue on Diversity in Multi Classifier Systems, 6(1):99-111, 2004.
  19. Learning Semantic Parsers: An Important But Under-Studied Problem
    [Details] [PDF]
    Raymond J. Mooney
    In Papers from the AAAI 2004 Spring Symposium on Language Learning: An Interdisciplinary Perspective, 39--44, Stanford, CA, March 2004.
  20. Relational Data Mining with Inductive Logic Programming for Link Discovery
    [Details] [PDF]
    Raymond J. Mooney, P. Melville, L. R. Tang, J. Shavlik, I. Dutra and D. Page
    Kargupta, H., Joshi, A., Sivakumar K., and Yesha, Y., editors, Data Mining: Next Generation Challenges and Future Directions:239--254, Menlo Park, CA, 2004. AAAI Press.
  21. Semisupervised Clustering for Intelligent User Management
    [Details] [PDF]
    Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney
    In Proceedings of the IBM Austin Center for Advanced Studies 5th Annual Austin CAS Conference, Austin, TX, February 2004.
  22. Semi-supervised Clustering: Learning with Limited User Feedback
    [Details] [PDF]
    Sugato Basu
    Technical Report, Cornell University, 2004.