We design a new technique for the distributional semantic modeling with a neural network-based approach to learn distributed term representations (or term embeddings) – term vector space models as a result, inspired by the recent ontology-related approach (using different types of contextual knowledge such as syntactic knowledge, terminological knowledge, semantic knowledge, etc.) to the identification of terms (term extraction) and relations between them (relation extraction) called semantic pre-processing technology – SPT. Our method relies on automatic term extraction from the natural language texts and subsequent formation of the problem-oriented or application-oriented (also deeply annotated) text corpora where the fundamental entity is the term (includes non-compositional and compositional terms). This gives us an opportunity to changeover from distributed word representations (or word embeddings) to distributed term representations (or term embeddings). The main practical result of our work is the development kit (set of toolkits represented as web service APIs and web application), which provides all necessary routines for the basic linguistic pre-processing and the semantic pre-processing of the natural language texts in Ukrainian for future training of term vector space models.
Against the backdrop of the development of modern technologies in the field of scientific research, the new class of Current Research Information Systems (CRIS) and related intelligent information technologies have arisen. It was called -Research and Development Workstation Environment (RDWE)the comprehensive problem-oriented information systems for scientific research and development lifecycle support. The given paper describes design and development fundamentals of the RDWE class systems. The general information model of the RDWE class systems is developed. Also the paper represents the information model of the RDWE class system for supporting research in the field of ontology engineeringthe automated building of applied ontology in an arbitrary domain area, scientific and technical creativitythe automated preparation of application documents for patenting inventions in Ukraine. It was called -Personal Research Information System. The main results of our work are focused on enhancing the effectiveness of the scientist's research and development lifecycle in the arbitrary domain area.На фоні розвитку сучасних технологій в сфері наукових досліджень, виник новий клас засобів комп'ютерних систем і відповідних інтелектуальних інформаційних технологій, що підтримують основні етапи життєвого циклу наукових досліджень. Цей клас систем отримав назву -Автоматизоване робоче місце наукових досліджень (АРМ-НД) -складні проблемно-орієнтовані інформаційні системи підтримки повного циклу наукових досліджень. В роботі наведено основи проектування і розробки систем класу АРМ-НД, розроблено узагальнену інформаційну модель систем класу АРМ-НД, а також наведена інформаційна модель розробленої АРМ-НД системи підтримки науково-технічної творчості та досліджень в області онтологічного інжинірингу. Отримані результати орієнтовані на підвищення ефективності повного науково-дослідного циклу роботи наукових співробітників в довільних предметних галузях. Ключові слова: АРМ-НД; АРМ; хмарне середовище; онтологічний інжиніринг; композитний веб-сервіс; хмарні обчислення; хмарне середовище навчання.На фоне развития современных технологий в сфере научных исследований, возник новый класс средств компьютерных систем и соответствующих интеллектуальных информационных технологий, поддерживающих основные этапы жизненного цикла научных исследований. Этот класс систем получил название -Автоматизированное рабочее место научных исследований (АРМ-НИ)сложные проблемно-ориентированные информационные системы поддержки полного цикла научных исследований. В работе описаны основы проектирования и разработки систем класса АРМ-НИ, разработана обобщённая информационная модель систем класса АРМ-НИ, а также описана информационная модель разработанной АРМ-НИ системы поддержки научно-технического творчества и исследований в области онтологического инжиниринга. Полученные результаты ориентированы на повышение эффективности полного научно-исследовательского цикла работы научных сотрудников. Ключевые слова: АРМ-НИ; АРМ; облачная среда; онтологический инжиниринг; композитн...
The monograph discusses certain aspects of modern real-world problems facing humanity, which are much more challenging than scientific ones. Modern science is unable to solve them in a fundamental way. Vernadsky’s noosphere thesis, in fact, appeals to the scientific worldview that needs to be built in a way that overcomes the interdisciplinary barriers and increases the effectiveness of interdisciplinary interaction and modern science overall. We are talking about the general transdisciplinary knowledge. In world practice, there is still no systematic methodology and a specific form of generally accepted valid scientific theory that would provide transdisciplinary knowledge. Non-linear interdisciplinary interaction is the standard of evolution of modern science. At the same time, a new transdisciplinary theory (domain of scientific research) is being de facto created and the process is repeated many times: from an individual or group of disciplines, through interdisciplinary interaction, in a direction that brings us closer to creating a holistic general scientific worldview.
One of the most effective solutions in medical rehabilitation assistance is remote patient / person-centered rehabilitation. Rehabilitation also needs effective methods for the “Physical therapist – Patient – Multidisciplinary team” system, including the statistical processing of large volumes of data. Therefore, along with the traditional means of rehabilitation, as part of the “Transdisciplinary intelligent information and analytical system for the rehabilitation processes support in a pandemic (TISP)” in this paper, we introduce and define: the basic concepts of the new hybrid e-rehabilitation notion and its fundamental foundations; the formalization concept of the new Smart-system for remote support of rehabilitation activities and services; and the methodological foundations for the use of services (UkrVectores and vHealth) of the remote Patient / Person-centered Smart-system. The software implementation of the services of the Smart-system has been developed.
This Letter to the Editor provides an update on the research from the Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine. The Institute’s research team in collaboration with Ternopil National Medical University began a new project called “Development of the cloud-based platform for patient-centered telerehabilitation of oncology patients with mathematical-related modeling.” The project is dedicated to the development of a hybrid cloud-based platform, and the creation on its basis of information technology for the telemedicine rehabilitation of cancer patients, and adapted for patients with combat stress disorder. The distinctive features of the proposed technology are a combination of artificial intelligence methods with accurate mathematical methods for optimization: developing mathematical models of problems of discrete, and non-smooth optimization, subgradient space transformation algorithms (to minimize non-smooth functions with tens of thousands of variables), and a method of global equilibrium search, etc.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.