HRecSys

HRecSys is a cloud-ready, Surprise powered recommendation system for hotels. Based on K-NN Algorithm.

Tech

• Python 3.7 - Lets you work quickly and integrate systems more effectively
• Surprise - Surprise is a Python scikit building and analyzing recommender systems.
• Joblib - A replacement for pickle to work efficiently on Python objects containing large data
• flask - Go WEB! Create REST endpoints for the application
• Docker - Enterprise Container Platform for High-Velocity Innovation
• Others like Pandas, NumPy, GeoPy, uWSGI, PyMysql

Database

For obvious reasons, the database connection is not provided for the application. There are two necessary tables for it:

user_hotel_rating

user_id	hotel_id	rating
12345	6731381	1
43256	4245612	3

hotel_data

hotel_id	latitude	longitude	guestRating	score	foodAndDrink	thingsToDo	...
6731381	51.507928	-0.176664	5	5	Full breakfast daily Restaurant	Outdoor seasonal pool Golf course on site	...
4245612	32.01234	1.123443	4.6	3	Restaurant Bar/lounge	Fitness facilities Full-service spa	...

And some more field, representing on the DatabaseHelper.py file

Installation

HRecSys easily runs on Docker.

$ cd HRecSys
$ docker build -t h_recsys .
$ docker run -i -t -p 80:80 h_recsys

Endpoints

There are two endpoint

URL	Method	Request	Response	Description
/retrain	POST	-	202 - {"retrain": done} or 5XX	Starts a retrain on the model
/recommend	POST	{ "userId": 12345, "coordinate": {"latitude": 51.514889,"longitude": -0.176835}}	200 - {"recommendations": 4245612, ...} or 5XX	Creats a set for the given location and predict recommendations (max 10)