Bag-of-words is a commonly used text representation method for many text classification applications. However, bag-of-words representation fails to consider the context of the text because it only examines text documents based on the presence of individual words and explores relationships between texts with similar word choices (Bengfort, 2018).…

The article is devoted to the trends and transformations of philological education in the context of modern technologies development. The purpose of the research is to study the preparation specifics of philology students and to develop a new approach to their training, based on an effective educational methodology of literary and linguistic…

The present research investigates how translators deal with the challenges of translating culture-specific words from Thai into English within a digital environment. Using strategies suggested by Baker (2018), the study collected data from surveys, written sources and observations to examine which approaches are used by translators. It also…

Computer systems tend to be ubiquitous as they become more integrated in our everyday activities, embedded in tables, shoes, watch and plenty of others connected things (CT). In the e-learning field, the transformations induced by the Internet of Things (IoT) allow individuals to learn whenever they want, accessing a quantity of diverse digital…

As we witness the prosperity of the social media in the past few years, and feel the explosion of "user-generated content" on the Internet, there is little question that we have entered an era of Big Data. Those social media sites, such as Facebook, LinkedIn, Quora and Twitter have been important sources for a wide spectrum of users.…

In the current millennium, extensive use of computers and the internet caused an exponential increase in information. Few research areas are as important as information extraction, which primarily involves extracting concepts and the relations between them from free text. Limitations in the size of training data, lack of lexicons and lack of…

Topic models like latent Dirichlet allocation (LDA) provide a framework for analyzing large datasets where observations are collected into groups. Although topic modeling has been fruitfully applied to problems social science, biology, and computer vision, it has been most widely used to model datasets where documents are modeled as exchangeable…

One of the problems associated with automatic thesaurus construction is with determining the semantic relationship between word pairs. Quasi-synonyms provide a type of equivalence relationship: words are similar only for purposes of information retrieval. Determining such relationships in a thesaurus is hard to achieve automatically. The term…

The present study is based on the theoretical assumptions that frequency of characters and their structural components, as well as the frequency types of structural components, are important to enable learners of Chinese as a foreign language (CFL) to discover the underlying structure of Chinese characters. In the CFL context, since reliable…

Purpose: The purpose of this paper is twofold: first the paper aims to sketch the theoretical basis for the use of electronic portfolios for prior learning assessment; second it endeavours to introduce latent semantic analysis (LSA) as a powerful method for the computation of semantic similarity between texts and a basis for a new observation link…

This article deals with the place of learner corpora, i.e. corpora containing authentic language data produced by learners of a foreign/second language, in English for academic purposes (EAP) pedagogy and sets out to demonstrate that they have a valuable contribution to make to the field. Following an initial brief introduction to corpus-based…