Guessing morphology from terms and corpora
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Corpus-based stemming using cooccurrence of word variants
ACM Transactions on Information Systems (TOIS)
A robust category guesser for Dutch medical language
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Automatic acquisition of two-level morphological rules
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
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Medical words exhibit a rich and productive morphology. Morphological knowledge is therefore very important for any medical language processing application. We propose a simple and powerful method to acquire automatically such knowledge. It takes advantage of commonly available lists of synonym terms to bootstrap the acquisition process. We experimented it on the SNOMED International Microglossary for pathology in its French version. The families of morphologically related words that we obtained were useful for query expansion in a coding assistant. Since the method does not rely on a priori linguistic knowledge, it is applicable to other languages such as English.