Please use this identifier to cite or link to this item:
https://dspace.univ-ouargla.dz/jspui/handle/123456789/20941
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | BOUACHA, Ismail | - |
dc.date.accessioned | 2019-06-25T08:41:47Z | - |
dc.date.available | 2019-06-25T08:41:47Z | - |
dc.date.issued | 2019-03-05 | - |
dc.identifier.uri | http://dspace.univ-ouargla.dz/jspui/handle/123456789/20941 | - |
dc.description | Le 2eme Conference Internationale sur intelligence Artificielle et les Technologies Information ICAIIT 2019 | en_US |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Université Kasdi Merbah Ouargla | en_US |
dc.relation.ispartofseries | 2019; | - |
dc.subject | Recommender System | en_US |
dc.subject | MovieLens | en_US |
dc.subject | Genetic Algorithm | en_US |
dc.subject | Similarity | en_US |
dc.title | A Genetic Based Recommender System | en_US |
dc.type | Article | en_US |
Appears in Collections: | 2. Faculté des nouvelles technologies de l’information et de la communication |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
BOUACHA Ismail.pdf | 506,33 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.