Abstract
The paper is devoted to the problem of the bibliometric study of publications on the topic “Cross-lingual Semantic Similarity”, available in the Dimensions database. Visualization of scientific networks showed fragmentation of research, limited interaction of organizations. Leading countries, leading organizations and authors are highlighted. Overlay visualization allowed us to assess the trends in citing authors. The expansion of the geography of research is shown. For international cooperation, the uniformity of semantic approaches to describing the concepts of critical infrastructure, incidents, resources and services related to their maintenance and protection is important. The stated approaches can be applied for visualization and modeling of technological development in the modern digital world. Semantic similarity is a longstanding problem in natural language processing (NLP). The semantic similarity between two words represents the semantic proximity (or semantic distance) between two words or concepts. This is an important problem in natural language processing, as it plays an important role in finding information, extracting information, text mining, web mining and many other applications.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
