Information Enrichment for Tourist Spot Recommender System Using Location Aware Crowdsourcing

Abstract

With the increase in number of available interesting locations, it becomes difficult for users to find interesting ones, thus imposes a need for recommender systems to suggest interesting locations. Further, to ease the user's decision making, the amount of supplementary information, such as right time to visit, weather conditions, traffic condition, right mode of transport, crowdedness, security alerts, etc., may be annotated with the list of recommended locations. This paper explores the possibility of enriching tourist locations using crowd sourcing approach, which can be used by Tourist Spot Recommender System (TSRS) for mobile users. Proposed crowd sourcing system focuses on getting work done from the crowd currently available at the location under consideration. In proposed system, the contributed information is not limited to ones available on blogs, web pages and sensor-readings from the device etc., but includes proactively-generated user's opinions and perspectives, that are processed to offer immediate knowledge. Our system works in collaboration with a TSRS, takes the list of locations to be recommended to the current user and performs just-in-time information enrichment for those selected set of locations. We have implemented a prototype of proposed systems using java android software development toolkit and evaluated this system by 76 real users.