Multi-word lexical units are a typical feature of specialized dictionaries, in particular monolingual and bilingual maritime dictionaries. The paper studies the concept of the multi-word lexical unit and considers the similarities and differences of their selection and presentation in monolingual and bilingual maritime dictionaries. The work analyses such issues as the classification of multi-w...

Word representation has always been an important research area in the history of natural language processing (NLP). Understanding such complex text data is imperative, given that it rich information and can be used widely across various applications. In this survey, we explore different word models its power expression, from classical to modern-day state-of-the-art (LMS). We describe a variety ...

This study reveals the influence of word mouth on destination reputation from perspective tourists’ judgment and explores differentiating effect dimensions degree consistency between based multinomial logistic regression analysis, aiming to advance theoretical exploration complex relationship reputation. finds that (1) tourists weigh word-of-mouth information is identical or different their vie...

Word processing systems ignore the fact that the history of a text document contains crucial information for its management. In this paper, we present database-based word processing, focusing on the incorporated document management system. During the creation process of a document, meta data are being gathered. This information is generated on the level of the whole document, on sections of a d...

Word embeddings are a powerful approach for unsupervised analysis of language. Recently, Rudolph et al. [35] developed exponential family embeddings, which cast word embeddings in a probabilistic framework. Here, we develop dynamic embeddings, building on exponential family embeddings to capture how the meanings of words change over time. We use dynamic embeddings to analyze three large collect...

The main goal of the present work is to explore the use of rich lexical information in language modelling. We reformulated the task of a language model from predicting the next word given its history to predicting simultaneously both the word and a tag encoding various types of lexical information. Using part-of-speech tags and syntactic/semantic feature tags obtained with a set of NLP tools de...