A recommendation engine for cafés

A recommendation engine for cafés

The aim of the project is to develop a recommendation system for customers in a cafe with mobile devices. QR code activates the menu and meanwhile the recommendation algorithm executes. The menu comes with recommendation labels. The customer orders from the menu and rate the items ordered while leaving. Collaborative filtering is popular among recommendation systems. However, it has some problems like dependency on human ratings, sparsity and cold start problem. In this project, we designed hybrid recommender system by combining user-based & memory-based collaborative filtering and some other techniques. As a result, we overcame the drawbacks of the collaborative filtering.

Project Poster: 

Project Members: 

Gözde Berk
Denizalp Kapısız

Project Advisor: 

Tunga Güngör

Project Status: 

Project Year: 

2017
  • Spring

Contact us

Department of Computer Engineering, Boğaziçi University,
34342 Bebek, Istanbul, Turkey

  • Phone: +90 212 359 45 23/24
  • Fax: +90 212 2872461
 

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