Please use this identifier to cite or link to this item:
https://dspace.univ-ouargla.dz/jspui/handle/123456789/20941
Title: | A Genetic Based Recommender System |
Authors: | BOUACHA, Ismail |
Keywords: | Recommender System MovieLens Genetic Algorithm Similarity |
Issue Date: | 5-Mar-2019 |
Publisher: | Université Kasdi Merbah Ouargla |
Series/Report no.: | 2019; |
Abstract: | In this paper we propose a genetic based recommender system. Our goal is to predict relevant items (films) from a huge space of data based on users ratings. We use MovieLens data set (which contains data on ratings made by users about films) to validate our approach. Our idea consists on finding for an active user, the most similar group of users using genetic algorithms. After that, we recommend items (films) based on prediction of the appreciation that the active user can give for each one. Several metrics have been used to prove the efficiency of our approach such Mean Absolute Error, precision and recall. |
Description: | Le 2eme Conference Internationale sur intelligence Artificielle et les Technologies Information ICAIIT 2019 |
URI: | http://dspace.univ-ouargla.dz/jspui/handle/123456789/20941 |
Appears in Collections: | 2. Faculté des nouvelles technologies de l’information et de la communication |
Files in This Item:
File | Description | Size | Format | |
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BOUACHA Ismail.pdf | 506,33 kB | Adobe PDF | View/Open |
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