Our primary research hypothesis stands on a simple idea: The evolution of top-rated publications on a particular theme depends heavily on the progress and maturity of related topics. And this even when there are no clear relations or some concepts appear to cease to exist and leave place for newer ones starting many years ago. We implemented our model based on Computer Science Ontology (CSO) and analyzed 44 years of publications. Then we derived the most important concepts related to Cloud Computing (CC) from the scientific collection offered by Clarivate Analytics. Our methodology includes data extraction using advanced web crawling techniques, data preparation, statistical data analysis, and graphical representations. We obtained related concepts after aggregating the scores using the Jaccard coefficient and CSO Ontology. Our article reveals the contribution of Cloud Computing topics in research papers in leading scientific journals and the relationships between the field of Cloud Computing and the interdependent subdivisions identified in the broader framework of Computer Science.
The main objectives of this paper are to discuss the various aspects of similarity calculations between objects and sets of objects in ontology-based environments and to propose a framework for cluster analysis in such an environment. The framework is based on the ontology specification of two core components: description of categories and description of objects. Similarity between objects is defined as an amalgamation function of taxonomy, relationship and attribute similarity. The different measures to calculate similarity that can be used in framework implementations are presented. The ontology-based data representation and the framework of cluster analysis can be useful in the area of Business Intelligence, e.g. clustering similar companies that profiles are described by ontology-based data.
The aim of this article is to determine whether there is a gap between the demand for competencies of graduates of the computer science major and their supply. Research Design & Methods: Identification of the key set of competencies required by employers from job applicants and estimation of the competency gap in the IT sector was conducted using the method of exploratory analysis of job offers for positions related to the administration of IT systems. Findings: The results of the preliminary research shown that proposed method can be used for estimation of competency gap however it requires more experiments. Contribution & Value Added: Proposition of new method for competency gap calculation based on exploratory analysis of data available in the Internet.
Methods of competency schema identification form the main topic of the paper. The survey of literature on the significance of competences on labour markets justifies the need for searching new methods and tools for performing labour market analysis. The authors propose competency schemas as a new tool for analysis competency demand existing on a given market. It seems that competency schemas can outperform competency profiles with respect to the scope of information which they can present. After presenting competency schemas concept, their application to analysis the situation on Polish labour market was discussed. The conclusions are formulated in the last part of the paper.
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