The service which enables us to use computing as a service across a product is known as cloud computing. Nowadays the cloud computing paradigm has been receiving significant excitement and attention in technological sphere. Cloud computing shares different resources and information between different devices which are located in different places always based on internet connection. According to this, a cloud DBMS is a database management system which acts through cloud computing. It is worth mentioning that the number of these DBMS which act through cloud computing is expected to increase in the future. Based on related research and results, there is an increment of interest in outsourcing of DBMS tasks to third parties that can afford these tasks with low and cheap cost. In this paper, we discuss about DBMS as a cloud service, advantages and disadvantages, opportunities and limitations, and we focus on the way how to offer a cloud DBMS as one of the best services. We focus on three main characteristics of cloud computing which are considered as the most worried issues of cloud platform. We review cloud database challenges such as: internet speed, multi-tenancy, privacy and security. We also focus on the way how to opposite these challenges in order to provide a successful cloud database. At the end of this paper we explain a specific architecture of cloud DBMS which is known as SCALEDB. We focus on its layer which this architecture contains and the way how these layers works. We thus express the need for a new DBMS, designed specifically for cloud computing environments.

Comparing textual content is becoming more and more problematic due to the fact that nowadays data is very dynamic. The application of sophisticated methods enables us to compare how similar the documents are to each other. In our research we apply the Cosine Similarity method to compare the similarity of several documents with each other. We also apply the TF-IDF technique which enables us to normalize the results. Normalization of these results is necessary for the fact that there are some words that are repeated several times and from this repetition is determined their importance. Finally we can see a comparison between the similarity of documents with normalized and non-normalized results. As can be seen in the research, the normalization of results has a great value in comparing documents with textual content.

Nowadays various types of data, especially those with public character, are stored and represented in relational databases. While this way of storing data is a practice for most of the institutions, it turns them into isolated silos with low level of accessibility and interoperability in the web. Indeed not all datasets are readable from the World Wide Web, therefore to increase their access it is necessary to provide mapping from relational databases to any serialization format of Resource Description Framework (RDF), as one of the best practices for distributing and interlinking data on the web. While there are several ways to accomplish the mapping process, the most appropriate and fastest way is by using the Protégé Plugins application. In this paper we present this mapping method, and describe the complete conversion of a database from SQL Server relational Database to RDF using different scenarios. By using Sesame Repository, as the local repository for our dataset, several SPARQL queries will be generated on top of our data. As a main contribution this paper emphasizes the advantages and performance of querying and using serialized RDF statements versus those stored in the relational databases.

No abstract

Technology plays a very important role in virtually all areas, and has become an inseparable part of the industry. Currently, industry and technology are at a high point of development and research, but there is an ever increasing gap between the market needs and the skills that universities deliver to students. There is an increasing need for consolidation between university curricula and the industry needs in terms of qualifications. In this paper we will present a description of the current state of the labor market in the field of technology, including the needs that arise in improving the existing curricula of the Universities. We review the different technologies that can be used, in order to automatically gather information about the market needs in terms of job offers, and how they can be compared against University curricula. We will also present the latest achievements on these methods, and the suggestions that the researchers provide.