Automatic Term Extraction Based on Perplexity of Compound Words

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.

• Type: Conference
• Year: 2005
• Where: IJCNLP
• Authors: Minoru Yoshida, Hiroshi Nakagawa
• Keywords: IJCNLP 2005, Many Methods, Method Combining Perplexity, Natural Language Processing, Small Corpus