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A proposed configurable approach for recommendation systems via data mining techniques |
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| Authors: | Ayman E Khedr Amira M Idrees Abd El-Fatah Hegazy Samir El-Shewy |
| Institution: | 1. Department of Information Systems, Faculty of Computers and Information, Helwan University, Cairo, Egypt;2. Department of Information Systems, Faculty of Computers and Information, Fayoum University, Fayoum, Egypt;3. College of Computing and Information Technology, AASTMT, Cairo, Egypt;4. Department of Management Information Systems, Modern Academy, Cairo, Egypt |
| Abstract: | This study presents a configurable approach for recommendations which determines the suitable recommendation method for each field based on the characteristics of its data, the method includes determining the suitable technique for selecting a representative sample of the provided data. Then selecting the suitable feature weighting measure to provide a correct weight for each feature based on its effect on the recommendations. Finally, selecting the suitable algorithm to provide the required recommendations. The proposed configurable approach could be applied on different domains. The experiments have revealed that the approach is able to provide recommendations with only 0.89 error rate percentage. |
| Keywords: | Recommendation systems clustering features’ selection data mining sampling |