Intelligent Travel Route Suggestion System Based on Pattern of Travel And Difficulties

Abstract

People travel a lot to new places for career, business, education, travel, health and for various other reasons. Travellers always search to find shortest and safest route to reach the destination. They majorly consider distance, modes of transport and safety as major parameters. Various algorithms, mechanisms are proposed earlier to serve the purpose. However existing algorithms, mechanisms suffer from various shortcomings like unable to analyze the suggestions and filtering the database. The existing models use collaborative or content filtering algorithms. These methods do not collect the past user experience. The main objective of this paper is to help the travellers from their source to target from a database with best possible way. Proposed method provides the information from the travellers and problems faced by them during their travel. Based on the reported issues and experiences, new path will be enrooted to the destination. In the proposed model C4.5 decision tree algorithm is used to collect data from previous user experience, minimum redundancy maximum relevance (MRMR) and features selection algorithm is used to reduce execution time and increase system accuracy. The experimental outcome of this paper is to improve the system accuracy and performance.