Search (7 results, page 1 of 1)

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Abstract

The first section of "Semantic Web and Education" surveys the basic aspects and features of the Semantic Web. After this basic review, the book turns its focus to its primary topic of how Semantic Web developments can be used to build attractive and more successful education applications. The book analytically discusses the technical areas of architecture, metadata, learning objects, software engineering trends, and more. Integrated with these technical topics are the examinations of learning-oriented topics such as learner modeling, collaborative learning, learning management, learning communities, ontological engineering of web-based learning, and related topics. The result is a thorough and highly useful presentation on the confluence of the technical aspects of the Semantic Web and the field of Education or the art of teaching. The book will be of considerable interest to researchers and students in the fields Information Systems, Computer Science, and Education.

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Abstract

The Entity-Relationship (ER) model is a fundamental formalism for conceptual modeling in database design; it was introduced by Chen in his milestone paper, and it is now widely used, being flexible and easily understood by practitioners. With the rise of the Semantic Web, conceptual modeling formalisms have gained importance again as ontology formalisms, in the Semantic Web parlance. Ontologies and conceptual models are aimed at representing, rather than the structure of data, the domain of interest, that is, the fragment of the real world that is being represented by the data and the schema. A prominent formalism for modeling ontologies are Description Logics (DLs), which are decidable fragments of first-order logic, particularly suitable for ontological modeling and querying. In particular, DL ontologies are sets of assertions describing sets of objects and (usually binary) relations among such sets, exactly in the same fashion as the ER model. Recently, research on DLs has been focusing on the problem of answering queries under ontologies, that is, given a query q, an instance B, and an ontology X, answering q under B and amounts to compute the answers that are logically entailed from B by using the assertions of X. In this context, where data size is usually large, a central issue the data complexity of query answering, i.e., the computational complexity with respect to the data set B only, while the ontology X and the query q are fixed.

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Date

24. 8.2016 14:03:22

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Date

17.12.2013 12:51:22

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Classification

006.7 22

Date

7. 3.2007 19:30:22

DDC

006.7 22

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Date

22. 5.2007 10:37:38