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  • × author_ss:"Angelova, G."
  1. Dobrev, P.; Kalaydjiev, O.; Angelova, G.: From conceptual structures to semantic interoperability of content (2007) 0.02 
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    Abstract
    Smart applications behave intelligently because they understand at least partially the context where they operate. To do this, they need not only a formal domain model but also formal descriptions of the data they process and their own operational behaviour. Interoperability of smart applications is based on formalised definitions of all their data and processes. This paper studies the semantic interoperability of data in the case of eLearning and describes an experiment and its assessment. New content is imported into a knowledge-based learning environment without real updates of the original domain model, which is encoded as a knowledge base of conceptual graphs. A component called mediator enables the import by assigning dummy metadata annotations for the imported items. However, some functionality of the original system is lost, when processing the imported content, due to the lack of proper metadata annotation which cannot be associated fully automatically. So the paper presents an interoperability scenario when appropriate content items are viewed from the perspective of the original world and can be (partially) reused there.
    Source
    Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a
    Type
    a
  2. Angelova, G.; Nenkova, A.; Boycheva, S.; Nikolov, T.: Conceptual graphs as a knowledge representation core in a complex language learning environment : a challenge for the conceptual graph approach (2000) 0.00 
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    Abstract
    This paper describes briefly the application of Conceptual Graphs (CG) in a tutoring environment for teaching English terminology and emphasises on knowledge acquisition results in the domain of finances. There are two important requirements imposed on the conceptual representation --- firstly, it should be clear and intuitive enough to be shown to the learner with pedagogic purposes and should allow for simple graphical visualisation and secondly, it should be sofisticated enough to serve as an input to a Natural Language Understanding (NLU) component, allowing analysis of the learners' answers. The possibilities to use one and the same knowledge base for both purposes are investigated and the paper shows that in a practically situated task-dependent paradigm, most ontological choices - granularity of concept types, conceptual relations, explicit and implicit concept hierarchy, are influenced by the task requirements
    Type
    a
  3. Hahn, W. von; Angelova, G.: Combining terminology, lexical semantics and knowledge representation in machine aided translation (1996) 0.00 
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