The application aims at solving one of the major problems in the aviation industry which is seating arrangement of people. We have tried to improve the in-flight experience of people by giving them seats next to like-minded people
Graph API is used to extract the data from the facebook profile of the said traveller
The Facebook profile link and permission to access it is provided by the user in either of the following ways:
During web check-in, the user can ask for seat recommendations and provide the facebook profile in the prompt
Frequent fliers can be asked about their interests through a form which is used by the airlines to store the information. At check-in counters, users can be asked for their social profile and a real-time prediction can be made The facebook BOT can also be used as a means to get interests
After social media analysis, all the users are divided into clusters according to their interests. Each cluster denotes different groups of like-minded people. When a person arrives he/she can be provided a seat with one of the people in the same cluster.
After determination of clusters, a matching algorithm is applied.
The matching algorithm assigns weights to different interests and assigns a score to each person in the corresponding cluster . The people with maximum matching scores and available adjoining can be provided with a seat with the current users.
Through this project, We learnt a little more insight about analysing the data and solving major problems by mining data and applying them in various machine learning models.
We hope this is the revolution in travel and we hope to diversify our models to twitter feeds and more feature sets.