|Project Description: ||The recent past showed a greater interest in recommender techniques. Now-a-days there are many travel packages existing from different websites to almost all the places over the world. A customer finds it very difficult to search for the best package as he/she has to browse multiple websites, contact many travel agents and etc. which is a tedious process and is time consuming. There should be a system where the user should find the best package on the Internet with a single click.
To address this issue, we adopt Travel Package Recommendation System which offers the best package among all the other packages that are on the web. This project will help tourist to suggest the best Travel Package among all the package deals on the web. On multiple demands of tourist that is, a customer will select a travel package for a particular place based on the recommendations provided by the previous customers who had experience with the package. Therefore, according to the personalized recommendations, he/she will choose the best package that is on the web.
Initially, we will evaluate the particular characteristics of the current traveling packages and we mine the data on the tourists rating and the intrinsic features i.e., locations, travel seasons etc. Based on the data collected after mining, we will generate a list for personalized travel package recommendations. Furthermore, we will extract the data based on the tourist's relation with the area and season.