A Concept Analysis Scheme of Simple Stories for Learning Resources through Extraction of Domain-based Multimedia Elements

Authors

  • Masoud U. Mwinyi Ph. D. Candidate, Qatar University
  • Jihad M. Alja'am Qatar University
  • Samir Abou El-Seoud British University in Egypt - BUE

DOI:

https://doi.org/10.3991/ijim.v11i2.6568

Keywords:

Keywords Extraction, Multimedia, Ontology, Special Education.

Abstract


Children with special needs face major difficulties to understand the script of stories. They cannot comprehend the words’ meaning properly. Instructors use different techniques to explain them. They read the script several times, use glossy images, symbols, and short clips. The instructors spend a lot of time searching for these elements. The preparation of every tutorial requires several hours of hard work. The objective of this work is to build a system to assist the instructor finding multimedia elements in real time that can be used during the learning sessions. The proposed system is based on a domain-oriented architecture focusing on animals and food. We use different techniques for text processing including concept analysis, key words extraction and sentence ranking. We can then determine the most significant words and sentences and generate the corresponding multimedia elements. Instructors and children can use smart devices in learning inside and outside the classroom.

Author Biographies

Masoud U. Mwinyi, Ph. D. Candidate, Qatar University

Ph. D. Candidate, Qatar University

Jihad M. Alja'am, Qatar University

Professor of Computer Science, Qatar University

Samir Abou El-Seoud, British University in Egypt - BUE

BUE, Informatics and Computer Science. Professor

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Published

2017-04-11

How to Cite

Mwinyi, M. U., Alja’am, J. M., & Abou El-Seoud, S. (2017). A Concept Analysis Scheme of Simple Stories for Learning Resources through Extraction of Domain-based Multimedia Elements. International Journal of Interactive Mobile Technologies (iJIM), 11(2), pp. 53–65. https://doi.org/10.3991/ijim.v11i2.6568

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Section

Papers