A search tool in Turkish using contextual vectors

Abstract

Natural Language Processing (NLP) field experienced considerable improvement in the year 2018. With the help of the transfer learning approach BERT (Bidirectional Encoder Representations) introduced by Google and approaches following it, state-of-the-art results were achieved in many NLP tasks. It became easier to research in this direction for Turkish with the help of published Turkish pre-trained BERT models in February, 2020. A new opportunity has arisen on research and development of contextual embeddings-based document retrieval instead of keyword-based for Turkish. This work introduces a BERT-contextual-vector-based Turkish text search tool. Sample queries and responses are presented to demonstrate the benefits it brings.