Akhil Chaudhary, Prajwal Mogaveera
Abstract: In order to provide reasonable as well as user-oriented result for this question, this model automatically observes famous and nearby places when someone visits some location and it will suggest useful information according to its current location, preferences, and past visits. Afterwards, the traveller guide allows for the user to provide feedback about each visit. The proposed solution is making use of machine learning techniques and recommendation systems to simplify the travel planning process for the end user. Various methods could be utilized to find patterns in given users past behaviour or to find similarities and correlations between known points of interest. These smart systems could be used to give personal experience and suggestions for user. These suggestions could be dependent on their schedule, preferences and budget. Machine learning would also automate the travel, its planning process and make the finding of the new impressive places easier for wider crowd of people.
Keywords: Random Forest, Bootstrap aggregating, Greedy algorithm, Bayesian algorithm for Information filtering, Smart information, Travel Information