Personal Work Space and Content Analysis Functionality in a Cultural Heritage Digital Library

The paper presents a different vision for personalization of the user’s stay in a cultural heritage digital library that models services for personalized content marking, commenting and analyzing that doesn’t require strict user profile, but aims at adjusting the user’s individual needs. The solution is borrowed from real work and studying of traditional written content sources (incl. books, manuals), where the user mainly performs activities such as underlining the important parts of the content, writing notes and inferences, selecting and marking zones of their interest in pictures, etc. In the paper a special attention is paid to the ability to execute learning analysis allowing different ways for the user to experience the digital library content with more creative settings.

Ontological Presentation of East-Christian Iconographical Art Domain

In the recent years the East-Christian iconographical art works have been digitized providing a large volume of data. The need for effective classification, indexing and retrieval of iconography repositories was the motivation of the design and development of a systemized ontological structure for description of iconographical art objects. This paper presents the ontology of the East-Christian iconographical art, developed to provide content annotation in the Virtual encyclopedia of Bulgarian iconography multimedia digital library. The ontology’s main classes, relations, facts, rules, and problems appearing during the design and development are described. The paper also presents an application of the ontology for learning analysis on an iconography domain implemented during the SINUS project “Semantic Technologies for Web Services and Technology Enhanced Learning”.

A Comparative Analysis of Predictive Learning Algorithms on High-Dimensional Microarray Cancer Data

This research evaluates pattern recognition techniques on a subclass of big data where the dimensionality of the input space (p) is much larger than the number of observations (n). Specifically, we evaluate massive gene expression microarray cancer data where the ratio κ is less than one. We explore the statistical and computational challenges inherent in these high dimensional low sample size (HDLSS) problems and present statistical machine learning methods used to tackle and circumvent these difficulties. Regularization and kernel algorithms were explored in this research using seven datasets where κ < 1. These techniques require special attention to tuning necessitating several extensions of cross-validation to be investigated to support better predictive performance. While no single algorithm was universally the best predictor, the regularization technique produced lower test errors in five of the seven datasets studied.

How Students Study? An Analysis of Learning Strategies in Engineering and Technology Courses

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

An Ontology-based Approach to Student Skills in Multiagent e-Learning Systems

The main idea of our approach is that the domain ontology is not only the instrument of learning but an object of examining student skills. We propose for students to build the domain ontology of examine discipline and then compare it with etalon one. Analysis of student mistakes allows to propose them personalized recommendations and to improve the course materials in general. For knowledge interoperability we apply Semantic Web technologies. Application of agent-based technologies in e-learning provides the personification of students and tutors and saved all users from the routine operations.

Recognition on Finite Set of Events: Bayesian Analysis of Generalization Ability and Classification Tree Pruning

The problem of recognition on finite set of events is considered. The generalization ability of classifiers for this problem is studied within the Bayesian approach. The method for non-uniform prior distribution specification on recognition tasks is suggested. It takes into account the assumed degree of intersection between classes. The results of the analysis are applied for pruning of classification trees.

Knowledge Learning Technology for Intelligent Tutoring Systems

In this work we suggest the technology of creation of intelligent tutoring systems which are oriented to teach knowledge. It is supposed the acquisition of expert’s knowledge by using of the Formal Concept Analysis method, then construction the test questions which are used for verification of the pupil's knowledge with the expert’s knowledge. Then the further tutoring strategy is generated by the results of this verification.

Cluster Analysis of Some Clases of Objects by Application of the Test Recognition Algorithms

The paper treats the task for cluster analysis of a given assembly of objects on the basis of the information contained in the description table of these objects. Various methods of cluster analysis are briefly considered. Heuristic method and rules for classification of the given assembly of objects are presented for the cases when their division into classes and the number of classes is not known. The algorithm is checked by a test example and two program products (PP) – learning systems and software for company management. Analysis of the results is presented.

Using the e-Class Open Platform for e-Learning Support at the TEI of Larissa, Greece

In the current paper we firstly give a short introduction on e-learning platforms and review the case of the e-class open e-learning platform being used by the Greek tertiary education sector. Our analysis includes strategic selection issues and outcomes in general and operational and adoption issues in the case of the Technological Educational Institute (TEI) of Larissa, Greece. The methodology is being based on qualitative analysis of interviews with key actors using the platform, and statistical analysis of quantitative data related to adoption and usage in the relevant populations. The author has been a key actor in all stages and describes his insights as an early adopter, diffuser and innovative user. We try to explain the issues under consideration using existing past research outcomes and we also arrive to some conclusions and points for further research.

An Approach to Variable Aggregation in Efficiency Analysis

In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.

Development of a Refactoring Learning Environment

This paper describes a Refactoring Learning Environment, which is intended to analyze and assess programming code, based on refactoring rules. The Refactoring Learning Environment architecture includes an intelligent assistant – Refactoring Agent, which is responsible for analysis and assessment of the code, written by students in real time by using a set of refactoring methods. According to the situation and based on the refactoring method, which should be applied, the agent could react in different ways. Its goal is to show the student, as much as possible, the weak places of his programming code and the possible ways to makes it better.

Provision of Mobile Learning in Higher Schools

Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013

Social - Oriented Applications of the Folklore Heritage for the Needs of the Non-formal Learning and Cultural Tourisms

The report presents a description of the most popular digital folklore archives in the world. Specifications for designing and developing web-based social-oriented applications in the field of education and cultural tourism are formulated on the basis of comparative analysis. A project for structuring and categorizing the content is presented. A website for accessing the digital folklore archive is designed and implemented.

Comparing Several Methods of Discriminant Analysis on the Case of Wine Data

2000 Mathematics Subject Classification: 62H30, 62J20, 62P12, 68T99

Automated Data Retrieval in Distance Learning Quality

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015