DC Field | Value | Language |
dc.contributor.author | BOUKHATEM, AHmed | - |
dc.date.accessioned | 2023-03-05T08:47:37Z | - |
dc.date.available | 2023-03-05T08:47:37Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | https://repository.esi-sba.dz/jspui/handle/123456789/405 | - |
dc.description | Supervisor: AMAR BENSABER
Djamel | en_US |
dc.description.abstract | In 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.iso | en | en_US |
dc.subject | Recommendation Systems | en_US |
dc.title | Recommendation System | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Master
|