Paper: NPMI Driven Recognition of Nested Terms

ACL ID W14-4805
Title NPMI Driven Recognition of Nested Terms
Venue CompuTerm International Workshop On Computational Terminology
Year 2014

In the paper, we propose a new method of identifying terms nested within candidates for the terms extracted from domain texts. The list of all terms is then ranked by the process of automatic term recognition. Our method of identifying nested terms is based on two aspects: grammatical correctness and normalised pointwise mutual information (NPMI) counted for all bigrams on the basis of a corpus. NPMI is typically used for recognition of strong word connections but in our solution we use it to recognise the weakest points within phrases to suggest the best place for division of a phrase into two parts. By creating only two nested phrases in each step we introduce a binary hierarchical term structure. In the paper, we test the impact of the proposed nested terms recognition method applied to...