Building a Recommender Agent for e-Learning Systems

By Osmar R Zaiane. IEEE International Conference on Consumer Electronics, 2002

438 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Science Applications, Information Systems

View Paper: https://www.semanticscholar.org/paper/d4d9bc2522c434b90427f655594e3ad42a66e204

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

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In Computer Science Applications

In Information Systems

Citations in the corpus

A model for measuring e-learning systems success in universities (2012, background): “Researchers’ experience Make it possible to ensure the presence of the students in the class (Artut, 2009; Chang & Chen, 2009; EL-Deghaidy & Nouby, 2008) Providing collaborative and active Learning (Zaïane, 2002) Possibility of evaluation of learning and performance”
Recommender system application developments: A survey (2015, methodology): “An e-learning recommender agent e-learning KB, Rule mining Web-based Individual 2002 [100]”
Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval (2008, background): “com in commercial systems [7], and smart recommenders in elearning [12], etc.”
Educational Data Mining: A Review of the State of the Art (2010, methodology): “Association-rule mining has been used to recommend online learning activities or shortcuts on a course website [293]; to”
Applying Data Mining Techniques to e-Learning Problems (2007, methodology): “Data Mining techniques such as Association Rule mining, and inter-session and intra-session frequent pattern mining, were applied in [98, 99] to extract useful patterns that might help educators, educational managers, and Web masters to evaluate and interpret on-line course activities.”
A Systematic Review on Educational Data Mining (2017, background): “the development of more sensitive and effective e-learning systems was studied by Zaıane [15].”
Recommender systems survey (2013, background): “The most common research papers are focused on movie recommendation studies [53,230]; however, a great volume of literature for RS is centered on different topics, such as music [134,162,216], television [238,18], books [164,88], documents [206,184,183,185], elearning [241,30], e-commerce [104,54], ”
Educational data mining: A survey from 1995 to 2005 (2007, background): “Some of the most promising work line is the use of e-learning recommendation agents (Lu, 2004; Zaı̈ane, 2002).”