State of Art Survey of Travel based Recommendation System

Abstract

Recommendation systems are software agents that can predict preference or interest of individual customers and recommend items accordingly. Online recommender system have been improved systematically in the last decade. With the booming of location sharing services, travel recommendation systems are also improving. Users share their geo-spatial dataset in social networks, inspired development of novel techniques and features in recommendation systems. Travel recommender system are emulation of offline travel agents. Travel based recommendation system provide users travel suggestions which helps in their decision making. This paper is a state-of -art survey of travel recommendation approaches. The merits and demerits of selected work is summarised and presented. Keywords: recommendation system, social network, LBSNs, point-of-interest, mobile-crowd-source.