| Autor: |
Ouassini, Mohamed |
| Přispěvatelé: |
Kurnaz, Sefer, Ouassini, Mohamed |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Popis: |
This study presents the development a recommendation system for an e-commerce based on Alternating Least Squares. This study explains the phases of creating sophisticated recommender systems and creates e-commerce platforms by using the best languages. Angular9 used for frontend, Python as backend, MongoDB as database and Flask as API. Different techniques are discussed in the study that can be utilized while developing an e-commerce. Collaboration filtering techniques are used in distributive recommender systems. Product metadata is used because all the information regarding dataset and customer can be stored in it and recommendation specialists can easily respond to the client query. Through this e-commerce sales representatives can easily view their products through graphs and get the relevant analytics. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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