Automated adaptive sequential recommendation of travel route

Big data has deeply rendered into both research and commercial fields such as health care, business and banking sectors. Automated Adaptive and Sequential Recommendation of Travel Route handovers automated and adaptive travel sequence recommendation from large amount of travel data. Unlike any other travel recommendation methods, this method is not only automated it is personalized to user's travel interest but also able to recommend a travel sequence rather than individual Points of Interest (POIs). This method has large amount of travel data including different places, the distributions of cost, visiting time and visiting season of each topic is mined to bridge the gap between user travel preference and travel routes and we also have topical package space. Here we use advantage of the complementary social media: community- contributed photos and map both user interests and travel data descriptions to the topical package space to get user topical package model and route. Representative images with viewpoint and seasonal diversity of POIs are shown to offer a more extensive impression.