کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
405333 677530 2011 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Learning task models in ill-defined domain using an hybrid knowledge discovery framework
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Learning task models in ill-defined domain using an hybrid knowledge discovery framework
چکیده انگلیسی

Domain experts should provide Intelligent Tutoring Systems (ITS) with relevant domain knowledge that enable it to guide the learner during problem-solving learning activities. However, for ill-defined domains this knowledge is hard to define explicitly. Our hypothesis is that knowledge discovery (KD) techniques can be used to extract problem-solving task models from the recorded usage of expert, intermediate and novice learners. This paper proposes a procedural-knowledge acquisition framework based on a combination of sequential pattern mining and association rules discovery techniques. The framework has been implemented and is used to discover new meta-knowledge and rules in a given domain which then extend domain knowledge and serve as problem space, allowing the Intelligent Tutoring System to guide learners in problem-solving situations. Preliminary experiments have been conducted using the framework as an alternative to a path-planning problem solver in CanadarmTutor.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 24, Issue 1, February 2011, Pages 176–185
نویسندگان
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