Real-time web-based International Flight Tickets Recommendation System via Apache Spark

Abstract

Traveling by airplane has become more popular with advanced technology. The tickets can be booked effortlessly via airlines corporation's online platforms. However, recommending the best airline ticket according to the buyer's demands is a challenging task owing to the unexpected fluctuations in the price depending on various reasons. Traditional recommender suggestions are optimized for predicting the price for a specific time or estimating the period of the lowest price. However, considering the sudden changes is an essential matter to increase the accuracy. In this work, we present a web-based real-time system to recommend the most suitable ticket regardless of the continuous changes in the prices. Apache Spark has been used to analyze the data obtained from the international airline web pages. Besides the ease of use of the system, it helps the customer to buy the flight ticket at the lowest price for the desired period and destination. Based on the proposed model, using Python programming language, Flask web server, and Apache Spark, we design and implement the international ticket recommendation system with the MVC design pattern.