PROJEKTOWANIE ORAZ ANALIZA FUNKCJI UOGÓLNIONEJ ARCHITEKTURY SYSTEMÓW HANDLU TREŚCIĄ ELEKTRONICZNĄ

This article is dedicated to the development of standardized methods and software for information resources processing in electronic content commerce systems (ECCS). In this paper an actual scientific problem of methods and tools development and research of information resources processing in ECCS was solved with the use of designed classification, mathematical tools, software and generalized ECCS architecture.Artykuł jest poświęcony rozwojowi znormalizowanych metod i oprogramowania do przetwarzania zasobów informacyjnych w systemach handlu treścią elektroniczną (ECCS). W artykule pokazano rozwiązania aktualnego problemu naukowego projektowania i badań przetwarzania zasobów informacyjnych w ECCS z wykorzystaniem metod i dedykowanych narzędzi matematycznych, oprogramowania i uogólnionej architektury ECCS

METHODS AND MEANS OF PROCESSING INFORMATION RESOURCES IN ELECTRONIC CONTENT COMMERCE SYSTEMS

This paper presents the development of unified methods and software tools for processing information resources in the electronic content commerce systems. A model of electronic content commerce systems is proposed. The models of information resource processing in electronic content commerce systems are proposed

SET-THEORETIC MODELS AND UNIFIED METHODS OF INFORMATION RESOURCES PROCESSING IN E-BUSINESS SYSTEMS

In the given article is functional logistic model of commercial content processing as the content life cycle stage in electronic commerce systems proposed. The model of commercial content processing describes the information resources forming in electronic content commerce systems and automation technology simplifies the commercial content mana-gement. In the given article the main problems of electronic content commerce and functional services of commercial content processing are analyzed. The proposed model gives an opportunity to create an instru-ment of information resources processing in electronic commerce systems and to implement the subsystem of commercial content formation, management and support

FEATURES OF THE CONTENT - ANALYSIS METHOD FOR TEXT CATEGORIZATION OF COMMERCIAL CONTENT IN PROCESSING ONLINE NEWSPAPER ARTICLES

This paper presents the features of text categorization of commercial content in linguistic modelling. Description of syntax sentence modelling is applied to automate the processes of analysis and synthesis of texts in natural language for commercial content categorization. This article suggests methods of content analysis for online newspaper. The model describes the processing of information resources systems of content analysis and simplifies the technology of content management system automation. General problems of syntactical and semantic content analysis and functional services of content management system are analysed

Онтологія аналізу Big Data

The object of this research is the Big Data (BD) analysis processes. One of the most problematic places is the lack of a clear classification of BD analysis methods, the presence of which will greatly facilitate the selection of an optimal and efficient algorithm for analyzing these data depending on their structure.In the course of the study, Data Mining methods, Technologies Tech Mining, MapReduce technology, data visualization, other technologies and analysis techniques were used. This allows to determine their main characteristics and features for constructing a formal analysis model for Big Data. The rules for analyzing Big Data in the form of an ontological knowledge base are developed with the aim of using it to process and analyze any data.A classifier for forming a set of Big Data analysis rules has been obtained. Each BD has a set of parameters and criteria that determine the methods and technologies of analysis. The very purpose of BD, its structure and content determine the techniques and technologies for further analysis. Thanks to the developed ontology of the knowledge base of BD analysis with Protégé 3.4.7 and the set of RABD rules built in them, the process of selecting the methodologies and technologies for further analysis is shortened and the analysis of the selected BD is automated. This is due to the fact that the proposed approach to the analysis of Big Data has a number of features, in particular ontological knowledge base based on modern methods of artificial intelligence.Thanks to this, it is possible to obtain a complete set of Big Data analysis rules. This is possible only if the parameters and criteria of a specific Big Data are analyzed clearly.Исследованы процессы анализа Big Data. Используя разработанную формальную модель и проведенный критический анализ методов и технологий анализа Big Data, построена онтология анализа Big Data. Исследованы методы, модели и инструменты для усовершенствования онтологии аналитики Big Data и эффективной поддержки разработки структурных элементов модели системы поддержки принятия решений по управлению Big Data.Досліджені процеси аналізу Big Data. Використовуючи розроблену формальну модель та проведений критичний аналіз методів і технологій аналізу Big Data, побудовано онтологію аналізу Big Data. Досліджено методи, моделі та інструменти для удосконалення онтології аналітики Big Data та ефективнішої підтримки розроблення структурних елементів моделі системи підтримки прийняття рішень з керування Big Data

FEATURES OF INFORMATION RESOURCES PROCESSING IN ELECTRONIC CONTENT COMMERCE

Some solutions of main problems of content e-commerce and content management services are described in the paper. Content lifecycle model in electronic commerce systems is considered. The model gives an opportunity to create effective tolls of information resources processing in electronic commerce systems and to implement the subsystem of commercial content formation, management and support

INFORMATION RESOURCES ANALYSIS IN ELECTRONIC CONTENT COMMERCE SYSTEMS

The article is dedicated to the development of unified methods and soft-ware tools for processing information resources in the electronic content commerce systems. A new detailed classification of electronic commerce systems and electronic content commerce systems is proposed. A formal model and generalized typical architecture of electronic content commerce systems are declared. Architecture and models of electronic content commerce systems are built

Онтологія аналізу Big Data

The object of this research is the Big Data (BD) analysis processes. One of the most problematic places is the lack of a clear classification of BD analysis methods, the presence of which will greatly facilitate the selection of an optimal and efficient algorithm for analyzing these data depending on their structure.In the course of the study, Data Mining methods, Technologies Tech Mining, MapReduce technology, data visualization, other technologies and analysis techniques were used. This allows to determine their main characteristics and features for constructing a formal analysis model for Big Data. The rules for analyzing Big Data in the form of an ontological knowledge base are developed with the aim of using it to process and analyze any data.A classifier for forming a set of Big Data analysis rules has been obtained. Each BD has a set of parameters and criteria that determine the methods and technologies of analysis. The very purpose of BD, its structure and content determine the techniques and technologies for further analysis. Thanks to the developed ontology of the knowledge base of BD analysis with Protégé 3.4.7 and the set of RABD rules built in them, the process of selecting the methodologies and technologies for further analysis is shortened and the analysis of the selected BD is automated. This is due to the fact that the proposed approach to the analysis of Big Data has a number of features, in particular ontological knowledge base based on modern methods of artificial intelligence.Thanks to this, it is possible to obtain a complete set of Big Data analysis rules. This is possible only if the parameters and criteria of a specific Big Data are analyzed clearly.Исследованы процессы анализа Big Data. Используя разработанную формальную модель и проведенный критический анализ методов и технологий анализа Big Data, построена онтология анализа Big Data. Исследованы методы, модели и инструменты для усовершенствования онтологии аналитики Big Data и эффективной поддержки разработки структурных элементов модели системы поддержки принятия решений по управлению Big Data.Досліджені процеси аналізу Big Data. Використовуючи розроблену формальну модель та проведений критичний аналіз методів і технологій аналізу Big Data, побудовано онтологію аналізу Big Data. Досліджено методи, моделі та інструменти для удосконалення онтології аналітики Big Data та ефективнішої підтримки розроблення структурних елементів моделі системи підтримки прийняття рішень з керування Big Data

World Universities Strategic Analysis Based on Data from the QS World University Rankings

The article examines indicators of influence on the overall ranking of world universities based on QS World University Rankings data, statistical analysis, smoothing methods, correlation analysis and forecasting. We considered the dynamic change of the Lviv Polytechnic National University rating. The identified trends and regularities, problems and advantages should serve as prerequisites for the development strategy of the worldwide universities, taking into account which will allow the formation of effective mechanisms for the long term. A study of the activities of universities was carried out, which made it possible to systematically, comprehensively and objectively comply with the requirements of information security, among which the confidentiality, integrity and availability of information are key, to determine the level of their potential opportunities and to develop a set of strategic directions and measures that contribute to their strategic development in perspectiv

Розроблення методу визначення стилю автора україномовних текстів на основі технологій лінгвометрії, стилеметрії та глоттохронології

We solved the problem of development of algorithmic software for processes of content monitoring for solving the problem of recognition of the style of an author of a Ukrainian text based on Web Mining and NLP technology. Decomposition of the method for recognition of the style of an author, based of analysis of the found stop words, was carried out. Specific features of the method include adaptation of morphological and syntactic analysis of lexical units to structural peculiarities of words/ texts in Ukrainian. It is syntactic words (stop words or anchor words) that are significant for an author’s individual style, as they are not related to the theme and content of the publication. Recognition of the author's style is based on analysis of coefficients of lexical author’s language: coherence of speech, lexical diversity, syntactic complexity indices of concentration and exclusivity for the author's fragment. They are used for subsequent comparison and determining of a degree of belonging of the analyzed text to a particular author. We studied internal "dynamics" of a text of randomly selected authors through analysis of coefficients of lexical author’s language for the first k, n and m (without the title) words of the author's fragment and the analyzed one. The obtained results were compared. We obtained results of experimental testing of the proposed method for content-monitoring for determining and analysis of stop words in Ukrainian scientific texts of technical area based on Web Mining technology. It was found that for the selected experimental base that contains 100 works, the method for analysis of an article without compulsory initial information and list of references attains the best results by density criterion. It is achieved through learning of the system and by checking specified blocked words and specified thematic vocabulary. Testing of the proposed method for determining of keywords from other categories of texts – of scientific humanitarian area, belles-lettres, journalistic, etc. – requires subsequent experimental research.Рассмотрены особенности применения технологий лингвометрии, стилеметрии и глоттохронологии для определения стиля автора публикаций. Лингвостатистический анализ авторского текста использует преимущества контент-мониторинга на основе методов NLP для определения стоповых слов. Квантитативный анализ стоповых слов использовано для определения степени принадлежности анализируемого текста конкретному автору. Предложен метод определения стиля автора украиноязычного текстаРозглянуто особливості застосування технологій лінгвометрії, стилеметрії та глоттохронології для визначення стилю автора публікацій. Лінгвостатистичний аналіз авторського тексту використовує переваги контент-моніторінгу на основі методів NLP для визначення стопових слів. Квантитативний аналіз стопових слів використано для визначення степеня приналежності аналізованого тексту конкретному авторові. Запропоновано метод визначення стилю автора україномовного текст