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MSCProject

Travel Destination Recommender Application with two approaches.

Version-1

RandomForestClassifier and Neural Network approach.

Application developed with Flutter asks for a set of inputs from user to make classification on server side running flask/Python with a trained model.

Version-2

Dynamic Recommender System .

First scoring function, asks for a trip option and makes recommendations by calculating cosine similarity between the type and the city description.

Second scoring function also asks for a trip option and then makes recommendation by calculating cosine similarity and also calcualting a final recommendation score by utilizing feedback from different forms.

Also a classifier is trained and implemented on the application to determine if user feedback is positive and negative.

Hotel_Reviews.csv file can be downloaded from here