Hotel Recommendation System with Machine Learning

We all plan trips and the first thing to do when planning a trip is finding a hotel. There are so many websites recommending the best hotel for our trip. In this article, I’m going to walk you through how to build a hotel recommendation system with Machine Learning with Python.

Hotel Recommendation System with Machine Learning

A hotel recommendation system aims to predict which hotel a user is most likely to choose from among all hotels. So to build this type of system which will help the user to book the best hotel out of all the other hotels. We can do this using customer reviews.

Also, Read – 200+ Machine Learning Projects Solved and Explained.

For example, suppose you want to go on a business trip, so the hotel recommendation system should show you the hotels that other customers have rated best for business travel. It is therefore also our approach to build a recommendation system based on customer reviews and ratings.

In the section below, I will take you through a project on Hotel Recommendation System with Machine Learning using Python programming language.

Hotel Recommendation System using Python

The dataset that I am using here is downloaded from Kaggle. As we are going to build a recommendation system according to the user ratings so here I will be using Natural Language Processing. Now let’s import the necessary Python libraries and the dataset to get started with the task of creating a hotel recommendation system:

hotel recommendation dataset
Note: The dataset contains more features

This dataset contains hotel data from 6 countries, namely:

  1. Netherlands
  2. United Kingdom
  3. France
  4. Spain
  5. Italy
  6. Austria

So for simplicity, I will change the name from “United Kingdom” to “UK. I can also see that there is no column as “Country” to specify the destination of the hotel but in the “Hotel_Address” column the last word mentioned is the name of the country. So I will extract the names of the countries from that column and store the name in a new column:

['Netherlands' 'UK' 'France' 'Spain' 'Italy' 'Austria']

Now I will drop the unnecessary columns that we don’t need for the task of creating a hotel recommendation system:

Now I will create a function to convert the strings of list into a normal list and then apply it to the “Tags” column in the dataset:

data after preparation

Now I will lowercase the “Tags” and “countries” column for simplicity:

data['countries'] = data['countries'].str.lower()
data['Tags'] = data['Tags'].str.lower()

Now let’s define a function to recommend the names of hotels according to the location and the description provided by the user. Here our aim is not just to recommend the name of the hotel but also rank it according to the user ratings:

Let’s See How It Works 😃

Now let’s test this function by selection any country out of the 6 countries mentioned in the dataset and describing the purpose of our trip and see how it works:

recommend_hotel('Italy', 'I am going for a business trip')
output of hotel recommendation system
recommend_hotel('UK','I am going on a honeymoon, I need a honeymoon suite room for 3 nights')

So we can see interesting results by the recommendation system. I hope you liked this article on how to create a recommendation system with Machine Learning using Python. Feel free to ask your valuable questions in the comments section below.

Aman Kharwal
Aman Kharwal

I'm a writer and data scientist on a mission to educate others about the incredible power of data📈.

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