Neuro-Fuzzy Based Classification of Web Courses Contents

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Research areas:
Year:
2014
Type of Publication:
Article
Keywords:
STRIPS, Planning, Neuro-Fuzzy, GATE, PDDL, Authoring Tools
Authors:
A. Abdel Whab; A. Nour Elmahdy; Ahmed Abdel Nabi; Hany Harb
Journal:
IJAIM
Volume:
2
Number:
4
Pages:
91-98
Month:
January
ISSN:
2320-5221
Abstract:
This paper presents a framework of an automated planning to the process of web course content configuration. The course plan is built by making use of STRIPS (Stanford Research Institute Problem Solver) which takes the initial knowledge and the target goal files from the learner and then gives the proposed plan. Two main parameters considered in the process are the starting knowledge that the learner already possesses and the target knowledge that is expected to be gained through the course in a text format. The initial and target knowledge are fed into the system to be transformed into weighted words using machine learning and information retrieval tools. A final total weight of the given subject is computed to be entered into neuro-fuzzy classifier to make the web course content plan. This approximate classification makes the planning process more powerful helping the learner to decide the starting or ending points of the web course.
Full text: IJAIM_204_Final.pdf

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