Statystyka i diagnostyka ekonomiczna
In: Prace naukowe Akademii Ekonomicznej imienia Oskara Langego we Wrocławiu 636
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In: Prace naukowe Akademii Ekonomicznej imienia Oskara Langego we Wrocławiu 636
Since 2010, the European Union countries have been implementing the objectives of the Europe 2020 Strategy aimed at smart, sustainable, and inclusive growth. The Strategy formulates nine indicators that are systematically monitored and assessed. Not all the indicators of the Europe 2020 Strategy could be used in the analysis in a direct way. Due to the limited availability and comparability of statistical data, this problem is presented in detail in part 2 of the article. The assessment of the achievement level of the Europe 2020 Strategy targets, both at the level of the entire European Union (the EU-level targets approach) and its individual Member States (the national-level targets approach) is the primary research purpose of the study. The composite index proposed and constructed on the basis of a dynamic relative taxonomy was used in the conducted research to present the diversified distance of the individual European Union countries in relation to the EU-level targets as well as the national-level targets of the Europe 2020 Strategy. The research methodology allows conducting the analysis taking into account the missing data. Most methods of ordering objects based on aggregate measures are compensatory in nature. This problem was significantly reduced by taking into account the geometric mean in the construction of the aggregate measure. The research findings revealed that in the years 2010–2019 an ongoing improvement in the implementation of both the EU and the national targets of the Europe 2020 Strategy was observed. In addition, the differences existing between the European Union Member States were reduced. However, none of the countries achieved the EU-level targets. Their highest implementation level was recorded in Denmark, Sweden, Austria, and Finland. The achievement level of the strategic goals regarding the national-level targets was influenced by the choice of one of the two approaches indicated in the study and adopted by the individual EU Member States in determining the set target values of the indicators, i.e., either prudential or optimistic.
BASE
In: Prace naukowe Akademii Ekonomicznej imienia Oskara Langego we Wrocławiu 658
In: Prace naukowe Akademii Ekonomicznej imienia Oskara Langego we Wrocławiu 524
In: Prace naukowe Akademii Ekonomicznej imienia Oskara Langego we Wrocławiu 487
In: Prace naukowe Akademii Ekonomicznej imienia Oskara Langego we Wrocławiu 447
In: Wiadomości statystyczne / Glówny Urza̜d Statystyczny, Polskie Towarzystwo Statystyczne: czasopismo Głównego Urze̜du Statystycznego i Polskiego Towarzystwa = The Polish statistician, Band 64, Heft 12, S. 7-26
ISSN: 2543-8476
The aim of the paper is to measure the scope and degree of differences in the situation of young people in the labour market in the border regions of Poland, the Czech Republic and Germany in 2010 and 2018, using six metric variables. For the purpose of the study, a hybrid approach was adopted, which involved carrying out linear ordering of the studied regions on the basis of the results of multidimensional scaling. The synthetic assessment of the changes in the situation of young people in the labour market in border regions was performed using the aggregate measure and Theil's decomposition. The study was based on data from Eurostat's REGIO database. It demonstrated that the situation of young people in the labour market in all the examined regions had significantly improved in the studied period. It also showed that Polish border regions, in addition to being significantly diversified in this respect, are in a worse situation than their German or Czech counterparts, but overall, the interregional disproportions among the countries shrank in the analysed period.
In: Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Heft 468, S. 13-19
ISSN: 2392-0041
In: Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Band 331
ISSN: 1899-3192
In: Studies in Classification, Data Analysis, and Knowledge Organization Ser.
Intro -- Preface -- Contents -- About the Editors -- Methodology -- 1 Evaluation of Two-Step Spectral Clustering Algorithm for Large Untypical Data Sets -- Abstract -- 1 Introduction -- 2 Limitations of Large Data Sets Classification -- 3 Proposal of New Algorithm -- 4 Simulation Experiment Results -- 5 Final Remarks and Conclusions -- References -- 2 Determining the Number of Groups in Cluster Analysis Using Classical Indexes and Stability Measures-Comparison of Results -- Abstract -- 1 Introduction -- 2 Measures of Cluster Stability -- 2.1 Ben-Hur and Guyon Stability Measure -- 2.2 Brock, Pihur, Datta, and Datta Stability Measure -- 2.3 Fang and Wang Stability Measure -- 3 A Data Set and the Scheme of Research -- 4 Empirical Results -- 4.1 Results for the Social Domain -- 4.2 Results for the Economic Domain -- 4.3 Results for the Environmental Domain -- 4.4 Results for the Institutional and Political Domain -- 5 Conclusions -- References -- 3 Identification of the Words Most Frequently Used by Different Generations of Twitter Users -- Abstract -- 1 Theory of Generations -- 2 Analysis of the Textual Data from the Social Network -- 2.1 Preparation of Text Data -- 2.2 Word Frequency Analysis -- 2.3 N-Gram Analysis -- 2.4 Agglomeration Methods of Hierarchical Clustering and Quality Assessment of Group Structure -- 3 Applications and Results -- 3.1 Twitter User Analysis -- 3.2 Analysis of the Words Occurring Most Commonly -- 3.3 Bigrams and Trigrams -- 4 Conclusion -- References -- 4 Classification Algorithms Applications for Information Security on the Internet: A Review -- Abstract -- 1 Introduction -- 2 Information Security -- 2.1 Cybersecurity Incidents Classification Taxonomy -- 2.2 Application on the Real Data -- 3 Methodology -- 4 Application of Classification Algorithms to Information Security -- 4.1 Popular Classification Algorithms.
In: Studies in classification, data analysis, and knowledge organization
In: Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Heft 384
ISSN: 2392-0041
In: PRACE NAUKOWE UNIWERSYTETU EKONOMICZNEGO WE WROCŁAWIU, Heft 507, S. 39-52
ISSN: 2392-0041
In: European research studies, Band XXIV, Heft Special Issue 3, S. 691-707
ISSN: 1108-2976
In: Studies in classification, data analysis, and knowledge organization
This volume presents a selection of peer-reviewed papers that address the latest developments in the methodology and applications of data analysis and classification tools to micro- and macroeconomic problems. The contributions were originally presented at the 30th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2021, held online in Poznan, Poland, September 810, 2021. Providing a balance between methodological and empirical studies, and covering a wide range of topics, the book is divided into five parts focusing on methods and applications in finance, economics, social issues and to COVID-19 data. The book is aimed at a wide audience, including researchers at universities and research institutions, PhD students, as well as practitioners, data scientists and employees in public statistical institutions.