Anna Rozeva

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• PhD
• Professor (Associate) at Technical University of Sofia

Abstract. In this chapter, we address security and privacy aspects in TeSLA, from a technical standpoint. The chapter is structured in three main parts. Firstly, we outline the main concepts underlying security in TeSLA, with regards to the protection of learners' data and the architecture itself. Secondly, we provide an empirical analysis of a spe...

In this chapter, we address security and privacy aspects in TeSLA, from a technical standpoint. The chapter is structured in three main parts. Firstly, we outline the main concepts underlying security in TeSLA, with regards to the protection of learners’ data and the architecture itself. Secondly, we provide an empirical analysis of a specific depl...

Choosing the appropriate architecture for a big data project is not a straightforward task. The architect needs to have knowledge in the problem domain, future application requirements, big data technology landscape and architectural patterns. Today’s dynamic business environment enforces constantly evolving big data applications, which often need...

eAssessment of students in engineering courses is specific due to the nature of the teaching, learning and examination process in technical education in general. Students need to write program codes, design electronic schemes, solve mathematical problems, analyze performance of engineering devices, describe solutions graphically, etc. Online assess...

Common opinion of educators in engineering education is the need for innovations in existing teaching and learning strategies by implementing the latest achievements of information and communication technologies (ICT) supporting teaching, learning and assessment processes. As employers’ requirements are constantly increasing, graduates need to get...

Trust in eAssessment is an important factor for improving the quality of online-education. A comprehensive model for trust based authentication for eAssessment is being developed and tested within the score of the EU H2020 project TeSLA. The use of biometric verification technologies to authenticate the identity and authorship claims of individual...

Checking the identity of students and authorship of their online submissions is a major concern in Higher Education due to the increasing amount of plagiarism and cheating using the Internet. The literature on the effects of e‐authentication systems for teaching staff is very limited because it is a novel procedure for them. A considerable gap is t...

Data analysis is an important issue for companies as it provides deep business insights thus facilitating their performance. Usually enterprise applications and platforms for Big Data processing live in the Java ecosystem. Therefore it is important to investigate how Java-based platforms for data analytics and machine learning work and the function...

Trust in eAssessment is an important factor for improving the quality of online-education. A comprehensive model for trust based authentication for eAssessment is being developed and tested within the scope of the EU H2020 project TeSLA. The use of biometric verification technologies to authenticate the identity and authorship claims of individual...

E‐assessment is a novel form to evaluate learners’ knowledge and skills in online education. Issues concerning security and privacy of learners’ data must be guaranteed. Such issues are discussed under the scope of the TeSLA project, a EU‐funded project that aims at providing learners with an innovative environment that allows them to take assessme...

Assessing the semantic similarity of texts is an important part of different text-related applications like educational systems, information retrieval, text summarization, etc. This task is performed by sophisticated analysis, which implements text-mining techniques. Text mining involves several pre-processing steps, which provide for obtaining str...

Choosing the appropriate architecture and technologies for a big data project is a difficult task, which requires extensive knowledge in both the problem domain and in the big data landscape. The paper analyzes the main big data architectures and the most widely implemented technologies used for processing and persisting big data. Clouds provide fo...

Starting from the general didactic goal of the learning process-achieving a sustainable qualitative learning process, the focus is on the characteristics of the assessment functions and their information provision in terms of interoperability. The objective of e-assessment according to TeSLA-project is to establish trust between students and lectur...

This work is performed in the scope of the TeSLA (An Adaptive Trust-based e-assessment System for Learning) project with the aim to investigate existing problems and solutions in e-assessment implemented in the engineering education, to present an overview of the best existing practice and to propose a blended assessment model consisting of offline...

Currently there is large quantity of content on web pages that is generated from relational databases. Conceptual domain models provide for the integration of heterogeneous content on semantic level. The use of ontology as conceptual model of a relational data sources makes them available to web agents and services and provides for the employment o...

Service-orientation for the development of complex distributed systems with reusable components (services) has proved to be highly beneficial approach in software engineering. In order to realize its advantages automated techniques and tools for finding services, selecting the ones that match requestor needs, composing them for achieving enhanced f...

The book presents selected papers in the fields of e-Governance centers and Universities, challenges e-Democracy, contemporary aspects and trends of e-Governance and design of knowledge and prediction models.

The research objective is to establish an approach for supporting the classification of text documents referring to a specified domain. The focus is on the preliminary topic assignment to the documents used for training the model. The method implements domain ontology as background knowledge. The idea consists in extracting the preliminary topics f...

The paper examines the problem of building ontologies in automatic and semi-automatic way by means of mining a dictionary database. An overview of data mining tools and methods is presented. On this basis an extended and improved approach is proposed which involves operations for pre-processing the dictionary database, clustering and associating da...

The book chapters have been compiled by selected technical papers resulting from the work on a project "Research and education centre for e-Governance", funded by the Bulgarian National Science Fund.

Deriving models for intelligent business analysis by generation of knowledge through data mining techniques has proved to be highly theoretically researched and practically implemented topic in the field of decision support and business intelligence systems in the last decade. A general data mining task concerns discovery and description of relatio...

The book highlights issues and practical research results in the field of e-Governance and open government, knowledge generation, sharing and dissemination of public administration and business management.

The aim of the paper is to present a framework for designing business model for knowledge generation from explicit data on "good" administrative management practices. Knowledge discovery demands the availability and access to high volumes of data. There is such data collected in databases and files in different formats. Knowledge extraction is perf...

Learning strategy in an intelligent learning system is generally elaborated on the basis of assessment of the following factors: learner’s time for reaction, content of the learning object, amount of learning material in a learning object, learning object specification, e‐learning medium and performance control. Current work proposes architecture f...

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e‐learning in an online learner‐centered environment. ILS is a distributed e‐learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e‐learning is achieved...

Hierarchies represent substantial part of the multidimensional view of data based on exploring measures of facts for business or non-business domain along various dimensions. In data warehousing and on-line analytical processing they provide for examining data at different levels of detail. Several types of hierarchies have been presented with issu...

The paper is dealing with data cubes, multidimensional data structures built from data warehouse for OLAP purposes. Performing aggregations over cube dimensions and the way they are stored is considered to be a problem worth optimization. A two-tier multilevel list structure for storing cubes has been proposed. Algorithms for tiers' setup and maint...

Star-join is a database scheme designed for the purpose of data warehousing. A typical query on a star-join scheme as well as an algorithm for its processing has been examined. An index structure for the star-join fact table has been proposed with the aim of facilitating template query processing. A multilevel index for the fact table's composite k...

AN OUTLOOK ON CURRENT ARCHITECTURE AND MODELS IN DATA MANIPULATION SYSTEMS Roumiana Tsankova, Anna Rozeva The form a group and the tipification of data manipulation system functions on levels is an input point in this research. The system functional characteristcs depend on user tasks only in external level. They join in several group in this leve...

A space model for data description and mathematical tools for data manirulation are discussed. The model is applicabled to hierarhically structured data.