Implementation Paper on Personalized Travel Recommendation by Mining People Attributes

Abstract

The recommendation system has growth choices in recent years. The recommendation system is existing in many applications which gives online travel information for individual travel package. A new model named travel recommendation using data mining techniques which extracts the features like locations, travel seasons of various landscapes. Thus, it possesses the material of the travel packages and interests of tourists. Further extending E-TRAST model with the tourist-relation-area season topic model includes relationship with tourists. It includes mining significant tourist locations based on the user search trajectories of users on web and also derives a personalized travel algorithm recommendation system using travelogues and users contributed photos with metadata of this photo by comparing existing different technique. To suggest personalized POI sequence, first famous routes are stratified as per the similarity between user package and route package. Keywords: Travel package, recommender systems, cocktail, topic modeling, and collaborative filtering