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Presenter : Cheng-Han Tsai

Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval. Presenter : Cheng-Han Tsai Authors : Mohamed Koutheair Khribi , Mohamed Jemni , Olfa Nasraoui ETS, 2009. Outlines. Motivation Objectives Methodology

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Presenter : Cheng-Han Tsai

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  1. Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval Presenter : Cheng-Han Tsai Authors : Mohamed KoutheairKhribi, Mohamed Jemni, OlfaNasraoui ETS, 2009

  2. Outlines • Motivation • Objectives • Methodology • Experiments • Conclusions • Comments

  3. Motivation • Most e-learning platforms are still delivering the sameeducational resources to learners • Most e-learning platforms have not been personalized

  4. Objectives • To build an automatic recommendations in e-learning platforms

  5. Methodology offline Learner model Content models CF&Cosine Similarity&Apriori algorithm&Association Rules&Confidence CBF & LOM&Inverted Index online CF + KNN&CBF + TF-IDF

  6. Methodology Learner model Confidence

  7. Methodology Content model Using the open source search engine Nutch in content model-ing followed by CBF Automatically generates invert-ed index

  8. Methodology

  9. Experiments

  10. Experiments

  11. Conclusions The proposed approaches can provide adaptive learning objects to different users The recommendation system can compute against massive repository of educational resources in "real time".

  12. Comments • Advantages • Integration of many approaches in this paper • Applications • IR

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