Planning a Trip: Route Recommendation System with Effective Query Keywords

Location-based social network (LBSN) services allow users to perform check-in and share their check-in data with their friends. In particular, when a user is traveling, the check-in data are in fact a travel route with some photos and tag information. In this proposed system, we focus on trip planning and intend to discover travel experiences from shared data in location based social networks. To facilitate trip planning, the prior works in provide an interface in which a user could submit the query region and the total travel time. Aim to discover travel experiences to facilitate trip planning. When planning a trip, users always have specific preferences regarding their trips. Instead of restricting users to limited query options such as locations, activities or time periods, consider arbitrary text descriptions as keywords about personalized requirements. Moreover, a diverse and representative set of recommended travel routes is needed. Prior works have elaborated on mining and ranking existing routes from check-in data. To meet the need for automatic trip organization, claim that more features of Places of Interest (POIs) should be extracted. Therefore, in this paper, Propose an efficient Keyword-aware Representative Travel Route framework that uses knowledge extraction from users' historical mobility records and social interactions. Explicitly, we have designed a keyword extraction module to classify the POI-related tags, for effective matching with query keywords.