• Submitted by: Bassel AlKhatib, Ammar Alnahhas, Firas Albadawi
    International Journal of Web-Based Learning and Teaching Technologies, 9(2), 1-13
    Date/Period: April-June 2014


    As text sources are getting broader, measuring text similarity is becoming more compelling. Automatic
    text classification, search engines and auto answering systems are samples of applications that rely on text
    similarity. Learning management systems (LMS) are becoming more important since electronic media is getting more publicly available. As LMS continuously needs content enrichment and the web is getting richer,
    automatic collection of learning materials becomes an innovative idea. Intelligent agents can be used with
    a similarity measurement method to implement the automatic collection process. This paper presents a new
    method for measuring text similarity using the well-known WordNet Ontology. The proposed method assumes
    that a text is similar to another if it represents a more specific semantic. This is more suitable for LMS
    content enrichment as learning content can usually be expanded by a more specific one. This paper shows
    how the hierarchy of WordNet can be taken advantage of to determine the importance of a word. It is also
    shown how similarity method within an e-learning system is exploited to achieve two goals. The first one is
    the enrichment of the e-learning content, and the second is the detection of semantically similar questions in
    e-learning questions banks.

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