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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/405
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dc.contributor.authorBOUKHATEM, AHmed-
dc.date.accessioned2023-03-05T08:47:37Z-
dc.date.available2023-03-05T08:47:37Z-
dc.date.issued2022-
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/405-
dc.descriptionSupervisor: AMAR BENSABER Djamelen_US
dc.description.abstractIn the recent years, recommendation systems have become extremely common. They can be used in many applications and circumstances to make ease of social life by generating categorized and personalized recommendations to the individuals. and It assists the customer to discover information and settle on choices where they do not have necessary knowledge to evaluate a specific item. Recommendation systems can be used as a part of different diverse approaches to encourage its customer with effective information sorting. It is a software tool and techniques that provide suggestions based on the customer’s taste to discover new appropriate things for them by filtering personalized data based on the user’s preferences from a huge volume of information. Users’ tastes and preferences should be accurately constructed in order to provide the most relevant suggestions. This paper compares, describes and details the various approaches of recommender systems and popular recommendation algorithms, as well as their applications.en_US
dc.language.isoenen_US
dc.subjectRecommendation Systemsen_US
dc.titleRecommendation Systemen_US
dc.typeThesisen_US
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