Using Semantic Patterns in Web Search and Assessment of Professionally Oriented Texts in a Foreign Language for Training Students in Higher Education Institutions of Mineral Resource Profile

Abstract

The article aims to analyse the possibility to use methods of web search and identification of semantic text patterns with a view to automatising the web search and assessment of professionally oriented texts used to train students at foreign language departments of higher education institutions of mineral resource development profile. The work provides an overview of relevant AI methods that may be employed to perform the tasks mentioned above and analyses a number of similar works. It offers a structure of patterns that can be used to find relevant research articles and describes approaches to assessment of the texts found. It also proposes the front-end structure of an application that can be tasked with web search and subsequent assessment of texts. The case study presents semantic analysis and assessment of a professionally oriented text written in English. The research done shows good prospects for using Semantic Web technologies for web search and assessment of texts available on the Internet not only for training students but also, in broader formulation, for teaching and learning in a chosen direction. This is ensured by flexibility of methods for semantic pattern search and identification. With respect to further development of the research, the authors consider designing an operational application for text search and assessment and also outcome analysis for a variety of directions of learning within the mineral resources development domain.