Citation

Huang H, Gartner G. J. Locat. Based Serv. 2012; 6(1): 1-21.

Copyright

(Copyright © 2012, Informa - Taylor and Francis Group)

DOI

10.1080/17489725.2011.625302

PMID

unavailable

Abstract

Mobile pedestrian navigation systems are one of the most popular Location-Based Services. In the era of Web 2.0, current mobile navigation systems often suffer from the following problems: the lack of social navigation support (utilizing other people's experiences) and the challenge of making user-generated content (UGC) useful. In this article, some collective intelligence-based route recommendation methods are designed to address these problems. The proposed methods can make use of UGC (reflecting other users' navigation experiences), and provide users with the least complex and the length-complexity-optimised (LCO) routes. Some simulations using the street network of the first district of Vienna (Austria) are designed to evaluate the proposed methods. The results show that compared to the shortest route, the collective intelligence-based routes (i.e. the least complex and the LCO routes) have a significant improvement of the route quality (with lower complexity ratings), thereby more effectively supporting users' navigation tasks (more chances of reaching the destination, fewer mistakes made and shorter distance traveled).