Lexical Acquisition: A Novel Machine Learning Problem (1996)
This paper defines a new machine learning problem to which standard machine learning algorithms cannot easily be applied. The problem occurs in the domain of lexical acquisition. The ambiguous and synonymous nature of words causes the difficulty of using standard induction techniques to learn a lexicon. Additionally, negative examples are typically unavailable or difficult to construct in this domain. One approach to solve the lexical acquisition problem is presented, along with preliminary experimental results on an artificial corpus. Future work includes extending the algorithm and performing tests on a more realistic corpus.
Technical Report, Artificial Intelligence Lab, University of Texas at Austin.

Raymond J. Mooney Faculty mooney [at] cs utexas edu
Cynthia Thompson Ph.D. Alumni cindi [at] cs utah edu