Research and Development Workstation Environment: the new class of Current Research Information Systems

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 has 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 RDWE class system's generalized information model is represented in the article as a three-tuple composite web service that include: a set of atomic web services, each of them can be designed and developed as a microservice or a desktop application, that allows them to be used as an independent software separately; a set of functions, the functional filling-up of the Research and Development Workstation Environment; a subset of atomic web services that are required to implement function of composite web service. In accordance with the fundamental information model of the RDWE class the system for supporting research in the field of ontology engineering - the automated building of applied ontology in an arbitrary domain area, scientific and technical creativity - the automated preparation of application documents for patenting inventions in Ukraine was developed. It was called - Personal Research Information System. A distinctive feature of such systems is the possibility of their problematic orientation to various types of scientific activities by combining on a variety of functional services and adding new ones within the cloud integrated environment. 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.Comment: In English, 13 pages, 1 figure, 1 table, added references in Russian. Published. Prepared for special issue (UkrPROG 2018 conference) of the scientific journal "Problems of programming" (Founder: National Academy of Sciences of Ukraine, Institute of Software Systems of NAS Ukraine

Application of Text Summarization techniques to the Geographical Information Retrieval task

Automatic Text Summarization has been shown to be useful for Natural Language Processing tasks such as Question Answering or Text Classification and other related fields of computer science such as Information Retrieval. Since Geographical Information Retrieval can be considered as an extension of the Information Retrieval field, the generation of summaries could be integrated into these systems by acting as an intermediate stage, with the purpose of reducing the document length. In this manner, the access time for information searching will be improved, while at the same time relevant documents will be also retrieved. Therefore, in this paper we propose the generation of two types of summaries (generic and geographical) applying several compression rates in order to evaluate their effectiveness in the Geographical Information Retrieval task. The evaluation has been carried out using GeoCLEF as evaluation framework and following an Information Retrieval perspective without considering the geo-reranking phase commonly used in these systems. Although single-document summarization has not performed well in general, the slight improvements obtained for some types of the proposed summaries, particularly for those based on geographical information, made us believe that the integration of Text Summarization with Geographical Information Retrieval may be beneficial, and consequently, the experimental set-up developed in this research work serves as a basis for further investigations in this field.This work has been partially funded by the European Commission under the Seventh (FP7-2007-2013) Framework Programme for Research and Technological Development through the FIRST project (FP7-287607). It has also been partially supported by a grant from the Fondo Europeo de Desarrollo Regional (FEDER), projects TEXT-MESS 2.0 (TIN2009-13391-C04-01) and TEXT-COOL 2.0 (TIN2009-13391-C04-02) from the Spanish Government, a Grant from the Valencian Government, project "Desarrollo de Técnicas Inteligentes e Interactivas de Minería de Textos" (PROMETEO/2009/119), and a Grant No. ACOMP/2011/001

Text Summarization Using Semantic Technique

This work proposes semantic technique as a new approach for text summarization of online news/ journal articles. This text summarization project contains two part: parsing and semantic analysis. At first, for the parsing, we set up criteria to evaluate importance of sentences within text such as position, length. According to this, only sentences with high score of importance will be selected. The number of sentence selected depends on how much compact that users expect summary output would be. System combines those sentences into summary draft. Second part is semantic analysis; the technique we use here is lexical semantic approach. During this part, system will use Word Net lexical database to analyze words within summary draft. This database had words linked through semantic relations such as synonym, antonym, hyponymy, and more. Our project would end up by evaluation process. We evaluate accuracy of summary output, also compare and find differences between human summary work and system result.