UTCS Artificial Intelligence
courses
talks/events
demos
people
projects
publications
software/data
labs
areas
admin
Lappoon R. Tang
Machine Learning Lab
:
Ph.D. Alumni
Neural Networks Lab
:
Undergraduate Alumni
Lappoon's research focuses on machine learning of natural language. As an undergraduate with the NNRG he worked on learning word representations from text corpora. He completed a PhD with the Machine Learning group on inductive logic programming applied to natural language processing and relational data mining.
Email:
ltang [at] utb edu
Homepage:
http://blue.utb.edu/ltang/
Publications
[Expand to show all 11]
[Minimize]
Relational Data Mining with Inductive Logic Programming for Link Discovery
2004
Raymond J. Mooney, P. Melville, L. R. Tang, J. Shavlik, I. Dutra and D. Page,
Data Mining: Next Generation Challenges and Future Directions
Kargupta, H., Joshi, A., Sivakumar K., and Yesha, Y. (Eds.) (2004), pp. 239--254. AAAI Press.
Integrating Top-down and Bottom-up Approaches in Inductive Logic Programming: Applications in Natural Language Processing and Relational Data Mining
2003
Lappoon R. Tang, PhD Thesis, Department of Computer Sciences, University of Texas.
Scaling Up ILP to Large Examples: Results on Link Discovery for Counter-Terrorism
2003
Lappoon R. Tang, Raymond J. Mooney, and Prem Melville, In
Proceedings of the KDD-2003 Workshop on Multi-Relational Data Mining (MRDM-2003)
, pp. 107--121, Washington DC, August 2003.
Relational Data Mining with Inductive Logic Programming for Link Discovery
2002
Raymond J. Mooney, Prem Melville, Lappoon R. Tang, Jude Shavlik, Inês de Castro Dutra, David Page, and Vítor Santos Costa, In
Proceedings of the National Science Foundation Workshop on Next Generation Data Mining
, Baltimore, MD, November 2002.
Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing
2001
Lappoon R. Tang and Raymond J. Mooney, In
Proceedings of the 12th European Conference on Machine Learning
, pp. 466-477, Freiburg, Germany 2001.
Automated Construction of Database Interfaces: Integrating Statistical and Relational Learning for Semantic Parsing
2000
Lappoon R. Tang and Raymond J. Mooney, In
Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora(EMNLP/VLC-2000)
, pp. 133-141, Hong Kong, October 2000.
Integrating Statistical and Relational Learning for Semantic Parsing: Applications to Learning Natural Language Interfaces for Databases
2000
Lappoon R. Tang, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Nested Expressions in Logic Programs
1999
Vladimir Lifschitz, Lappoon R. Tang and Hudson Turner,
Annals of Mathematics and Artificial Intelligence
, Vol. 25 (1999), pp. 369-389.
An Experimental Comparison of Genetic Programming and Inductive Logic Programming on Learning Recursive List Functions
1998
Lappoon R. Tang, Mary Elaine Califf, and Raymond J. Mooney, Technical Report AI 98-271, Artificial Intelligence Lab, University of Texas at Austin.
Learning to Parse Natural Language Database Queries into Logical Form
1997
Cynthia A. Thompson, Raymond J. Mooney, and Lappoon R. Tang, In
Proceedings of the ML-97 Workshop on Automata Induction, Grammatical Inference, and Language Acquisition
, Nashville, TN, July 1997.
A Connectionist Corpus-Based Approach to the Building of Word Representations
1994
Rupert L. Tang, Technical Report HR-94-01, Department of Computer Science, The University of Texas at Austin.
Projects
Learning Word Meanings: The FGREP Method
1987 - 1994
Areas of Interest
Concept and Schema Learning
Natural Language Processing (Cognitive)
Software/Data
FGREPNET
The FGREPNET package contains the C-code and data for training and testing an FGREP network in developing distributed re...
1994
Labs
Formerly affiliated with
Machine Learning
Formerly affiliated with
Neural Networks