Corpus-driven hyponym acquisition for Turkish language

In this study, we propose a method for acquisition of hyponymy relations for the Turkish Language. This integrated method relies on both lexico-syntactic pattern and semantic similarity. Once the model has extracted the items using patterns it applies similarity based elimination of the incorrect ones in order to increase precision. We show that the algorithm based on a particular lexico-syntactic pattern for Turkish language can retrieve many hyponymy relations and also demonstrate that elimination based on semantic similarity gives promising results. We discuss how we measure the similarity between the concepts. The objective is to get better relevance and more precise results. The experiments show that this approach gives successful results with high precision. © 2012 Springer-Verlag.