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Authors Information Polina Valkova e-mail valkova99 yahoo. com Irina Zheliazkova e-mail irina ecs. ru. acad.bg University of Rousse Rousse 7017 Studentska street 8 Bulgaria MODELS TECHNIQUES AND APPLICATIONS OF E-LEARNING PERSONALIZATION Desislava Paneva Yanislav Zhelev Abstract In recent years Web has become mainstream medium for communication and information dissemination. This paper presents approaches and methods for adaptive learning impl...

To achieve this, they build on the model of 'syntax-as-semantics' by R. D'Alton and A. Began and on the proposed framework of 'methodology' (see Section 3.2). They define the concept of the 'level' in the semantic graph, for instance between language and its components. To represent domain contents themselves, they propose a 'meta-domain' which models the content of the system. Their approach to understanding a higher level of structure is based on a 'structural analysis methodology' aiming to identify subcomponents of higher levels. In particular, the methods address three main types of knowledge representation, a conceptual representation of meaning and a 'syntactic analysis of word forms'. The analysis is performed in the first stage through an approach based on the idea of a 'syntactic graph', on which the author builds a model based on the concept of 'semantic decomposition'. The authors show that syntactic decomposition has the advantage of being able to represent a large variety of semantic relationships. The third step is based on a domain-based approach aiming to identify the components of a level, and their use. Keywords: Semantic decomposition, domain components, ontologies, structured knowledge 1. Introduction In many ways, the structure of courseware is similar to the structure of domain-specific knowledge in other domains [Ferguson, 2002]. The main difference concerns the fact that the latter are typically designed to suit the intended domain [Ferguson, 2002]. There are two important approaches on how to represent domain-specific knowledge in general. The first one is that of the concept-language (C) approach, designed to represent domain knowledge in a more formal manner, e.g. by using concepts, expressions or predicates [Munroe-Smith, 1999; Munroe-Smith & Fennel, 2004; Fennel & Munroe-Smith, 2009). The second one is the ontology-based approach, designing a graph (D) to represent domain knowledge in an informal, less formal way, e.g. using domain terminology [Stoyanov & Altova, 2007]. It is well known that ontologies of knowledge based on concepts help to understand how domain knowledge works.

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