We started by focusing our attention to restaurants, i.e. places in which people can have dinner with friends, relatives and other people. Instead of collecting one rating for each restaurant, expressing the overall preference for the place, we let our users specify if they like or not a place according to different situations, that we call purposes:

• bringing out some visitors;
• having a romantic dinner with their partner;
• going out with friends;
• for a lunch break (where price/quality ratio is important).

Thanks to these different ratings, we can better understand people tastes and focus our recommendations to the particular purpose for the user's choice of the place.

The recommendations it provides are quickly computed and easy to consume, reducing the search time from the usual 30 minutes to analyze a long list of restaurants to 30 seconds to identify the best restaurant for you in a very short and precise recommendation list. The recommended restaurants are shown one by one, so you can immediately get all the needed information to decide whether the place is perfect for you or you should check the next one. The applied algorithm has been demonstrated to better combine speed and precision.

The recommended restaurants are not just the best for YOU (thanks to personalization of results) but are also the best ones according to your current needs: different results are shown depending on your companions (i.e. tourists, the partner or friends) or on your time/budget constrains (i.e. lunch break).

Need one more reason for trying a new restaurant? Check if it offers coupons and enjoy your dinner with free or discounted extras.

This project has been interrupted right before its publication as the company that was funding it, Trento Rise, had serious financial problems and closed.

Screenshots

Planfree has been implemented as a web service with a responsive website, adapting to both desktops and mobiles, as user interface.

A couple of screenshots of the website viewed from desktop

Screenshots of the website viewed from mobile

Team and Implementation

The team was composed of different members:

• Prof. Fabio Casati - Researcher
• Dr. Florian Daniel - Researcher
• Beatrice Valeri - Researcher and Developer
• Alessia Gasperi - Designer

Planfree is composed of the following components:

• Cloud: Google App Engine
• Backend: Python + Datastore + Google Cloud SQL
• Responsive website: Python Jinja2 + HTML/CSS + Javascript(JQuery, underscore)