PRACTICAL APPLICATION OF SELECTED DATABASE SYSTEMS IN NATURAL LANGUAGE PROCESSING
According to the 2017 curriculum, the database is one of the key components of Information Technology knowledge area. First- and second-level students are taught the theory as well as practical use of databases. Their applications are of great importance at technical universities, equipping students with skills that are so needed in their future careers.
Relational databases, e.g. MySQL or PostgreSQL, have many practical uses, both in education, research and industry. They are used for storing data for web and mobile applications, as well as geographic objects or text. They are one of the most popular open-source object-relational database systems, appreciated for stability, reliability and continuous development. This is why these databases were chosen for storing n-grams.
The n-gram is a sequence of consecutive units such as words, syllables, phonemes, sounds or letters. The division into n-grams can be used for single words as well as whole sentences. This method is commonly used for word processing, in particular for translating and correcting errors, identifying the language used for writing, compressing text and many others. The advantage of this method is that it can be used with any text, regardless of its language.
The aim of this paper is to present the idea of storing n-grams in database systems. The structure of the database and its practical use is shown. This practical aspect of combining database together with n-grams is an example of a link between education and research. By using such technology-enhanced learning, the students may increase both their practical skills of database management and the ability to perform research with n-grams. Such practical use of databases may be a basis for a larger tool for performing students’ research on connecting natural language processing with the database tool.
On the ICT labour market there is a great demand for database specialists. The proposed solution may increase the number of students with database experience and natural language processing skills, and thus allow them to enter the labour market more easily.