Foundations of statistical natural language processing
Foundations of statistical natural language processing
Extended models and tools for high-performance part-of-speech tagger
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
A methodology for automatic term recognition
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Automatic extraction of bilingual terms from a Chinese-Japanese parallel corpus
Proceedings of the 3rd International Universal Communication Symposium
Hi-index | 0.00 |
Many methods of term extraction have been discussed in terms of their accuracy on huge corpora. However, when we try to apply various methods that derive from frequency to a small corpus, we may not be able to achieve sufficient accuracy because of the shortage of statistical information on frequency. This paper reports a new way of extracting terms that is tuned for a very small corpus. It focuses on the structure of compound terms and calculates perplexity on the term unit's left-side and right-side. The results of our experiments revealed that the accuracy with the proposed method was not that advantageous. However, experimentation with the method combining perplexity and frequency information obtained the highest average-precision in comparison with other methods.