Text Categorization and Clustering
The ability to categorize natural-language documents and web pages into known categories using supervised learning or to cluster them into meaningful new categories using unsupervised learning has important applications in information retrieval, information filtering, knowledge management, and recommender systems. Our research has focused on applications of text learning to recommender systems and on semi-supervised clustering of documents.
Shruti Bhosale Formerly affiliated Masters Student shruti [at] cs utexas edu
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Detecting Promotional Content in Wikipedia 2013
Shruti Bhosale, Heath Vinicombe, and Raymond J. Mooney, In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), pp. 1851--1857, Seattle, WA, October 2013.
Multi-Prototype Vector-Space Models of Word Meaning 2010
Joseph Reisinger, Raymond J. Mooney, In Proceedings of the 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-2010), pp. 109-117 2010.
Spherical Topic Models 2010
Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond J. Mooney, In Proceedings of the 27th International Conference on Machine Learning (ICML 2010) 2010.
Spherical Topic Models 2009
Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond Mooney, In NIPS'09 workshop: Applications for Topic Models: Text and Beyond 2009.
Probabilistic Semi-Supervised Clustering with Constraints 2006
Sugato Basu, Mikhail Bilenko, Arindam Banerjee and Raymond J. Mooney, In Semi-Supervised Learning, O. Chapelle and B. Sch{"{o}}lkopf and A. Zien (Eds.), Cambridge, MA 2006. MIT Press.
Model-based Overlapping Clustering 2005
A. Banerjee, C. Krumpelman, S. Basu, Raymond J. Mooney and Joydeep Ghosh, In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-05) 2005.
Semi-supervised Clustering: Probabilistic Models, Algorithms and Experiments 2005
Sugato Basu, PhD Thesis, University of Texas at Austin.
A Probabilistic Framework for Semi-Supervised Clustering 2004
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), pp. 59-68, Seattle, WA, August 2004.
Active Semi-Supervision for Pairwise Constrained Clustering 2004
Sugato Basu, Arindam Banerjee, and Raymond J. Mooney, In Proceedings of the 2004 SIAM International Conference on Data Mining (SDM-04), April 2004.
Semi-supervised Clustering with Limited Background Knowledge 2004
Sugato Basu, In Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, pp. 979--980, San Jose, CA, July 2004.
Semi-supervised Clustering: Learning with Limited User Feedback 2004
Sugato Basu, Technical Report, Cornell University.
Semi-supervised Clustering by Seeding 2002
Sugato Basu, Arindam Banerjee, and Raymond J. Mooney, In Proceedings of 19th International Conference on Machine Learning (ICML-2002), pp. 19-26 2002.
Content-Based Book Recommending Using Learning for Text Categorization 2000
Raymond J. Mooney and Loriene Roy, In Proceedings of the Fifth ACM Conference on Digital Libraries, pp. 195-204, San Antonio, TX, June 2000.
Content-Based Book Recommending Using Learning for Text Categorization 1999
Raymond J. Mooney and Loriene Roy, In Proceedings of the SIGIR-99 Workshop on Recommender Systems: Algorithms and Evaluation, Berkeley, CA, August 1999.
Using HTML Structure and Linked Pages to Improve Learning for Text Categorization 1999
Michael B. Cline, Technical Report AI 98-270, Department of Computer Sciences, University of Texas at Austin. Undergraduate Honors Thesis.
Book Recommending Using Text Categorization with Extracted Information 1998
Raymond J. Mooney, Paul N. Bennett, and Loriene Roy, In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98)"-REC-WKSHP98, year="1998, pp. 70-74, Madison, WI 1998.
Text Categorization Through Probabilistic Learning: Applications to Recommender Systems 1998
Paul N. Bennett, unpublished. Honors thesis, Department of Computer Sciences, The University of Texas at Austin.