A Mobile based Travelling Recommendation Framework with the Big Five Personality Model

Abstract

Currently, a lot of travelling recommendation systems use reviews and ratings to give a recommendation. Some of the reviews are paid reviews. This paper aims at presenting a personality based recommendation framework in travelling that recommends places of interest based on the user’s personality. The items to be recommended can be any objects such as hotels, restaurants, attraction places, etc. We applied the Big Five Personality test which consists of openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism to capture the personality of the users. The Big Five Personality test has 15 statements and a scale of 1 to 7 on how much the user agrees with the statement. At the end of the test, a score is calculated for each trait by calculating its mean value. The similarity between the user’s personality score with other users’ personality scores is then measured. Places of interest are recommended based on the personality similarities between the users.