Feelings' Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and Crowdsourcing

Abstract

In this paper, an innovative geographical locations' rating scheme is presented, which is based on crowdsensing and crowdsourcing. People sense their surrounding space and submit evaluations through: (a) a smartphone application, and (b) a prototype website. Both have been implemented using the state-of-the-art technologies. Evaluations are pairs of feeling/state and strength, where six different feelings/states and five strength levels are considered. In addition, the detection of similar locations is proposed by maximizing a cross-correlation criterion through a genetic algorithm approach. Technical details of the overall system are provided so that the interested readers can replicate its components. The experimental results on real-world data, which also include comparisons with Google Maps Rating and Tripadvisor, illustrate the merits and limitations of each technology. Finally, the paper is concluded by uncovering and discussing interesting issues for future research.