Main Article Content
Background: A vast geotagged data that is generated through online as a result of advanced data sharing services and massive mobile technologies. The features of this data create a new technique for researchers in the tourist sector and hospitality to analyse traveller movement and behaviour.
Objectives: To examines existing geotagging research and todevelop an optimal technique for creating metadata for geotagging data in social networks.
Methods: Five different categories have been identified and prospective geotagging research issues in tourism and hospitality are also been noted. Further we propose the method in which the traditional Travelling Salesmen Problem(TSP) has been tweaked with machine learning algorithm to provide an optimized solution for travellers.
Results:This method can give better average gap then the existing method.
Conclusions:In this paper we have also proposed a methodology that uses polished Bert technique that analysis the path efficiently. This method can also give better average gap then the existing method.