Metadata Extraction and Description with Use of RDF for e-Learning Context

M. Maejima and Y. Tamura (Japan)


Natural Language Processing, Case Analysis, Deep Case, RDF, and Metadata


This paper proposes a method to transform e-Learning context of Japanese natural language description into a RDF formal description with use of a case frame. With use of the case frame, more precise representation of meaning and relationship between words of the given sentence is available, rather than a collection of keyword. Also the authors adopt the RDF for formal description, because it provides machine-readable and interpretable representation of the given sentences. An author or editor just writes some key sentences for each e-Learning contents. The proposing system processes them and generates the RDF description automatically. It will benefit to search suitable e-Learning content.

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