Travel Route Recommendation System using Big-Multisource Social Media: A Survey

Abstract

In the era of internet, social media has become a big boom for Internet users. These users used to share their dayto-day activities on social media sites like Facebook, Twitter, Flicker and so on. Different data gets uploaded related to users activities like check-ins, GPS locations, tagging friends, travel routes, shopping, dining and photos. The comfort of user convenience has resulted in tremendously increased user count of the Internet. Simultaneously, it is also leading to building of information as a huge database of places, routes, services etc. Considering these all things, our targeted work is to build an enhanced travel advisory and recommendation system. Such a system gives complete freedom to users for choosing their suitable trip options. The users gets able to fetch complete information like statistics of users visited given place, available facilities and most importantly preferred travel routes. All this information can have associated cost options for ease of decision-making. With the help of social media activities like recommendations, likes/dislikes, posts, shares, tags and check-in information, it can build automatic trip advisor to provide better travelling experience with cost-saving and user convenient features. This diverse database can provide features like text-based and pictorial search module. Thus the available maps and locations help users to synchronize their actions with existing routes along with probable route restructuring functionality. Also uses can use the combination of skyline representative concepts and keyword extraction module for appropriate decision making to choose the best place from multiple Places-of Interest (POIs).