Martin Traunmueller
Johannes Schöning
Duncan P. Brumby
ABSTRACT
Most (mobile) online map services focus on providing their users the most efficient route to their target location. In this paper we investigate the relationship between the physical and digital urban navigation to improve wayfinding for pedestrians by enhancing their experiences when strolling through a city. With our application "Space Recommender System" we describe a new wayfinding approach by implementing common digital online methods of commenting and recommender systems into the physical world, using voting data from social network services. Initial findings highlight the general importance of the walking experience to the public and suggest that implementing social media based recommendations in route finding algorithms enhance the pleasure of urban strolling. The initial user tests of the system in a real world context together with collected feedback and the observations throughout the design process stimulate the discussions of wider issues and highlight its potential for future novel wayfinding applications.
- Dörk, M., Carpendale, S. & Williamson, C. The Information Flaneur: A Fresh Look at Information Seeking, In Proc. CHI 2011 ACM (2011) 1215--1224 Google Scholar
Digital Library
- Kirman, B., Linehan, C., Lawson, S., Get lost: facilitating serendipitous exploration in location-sharing services, In Proc CHI'12, ACM Press (2012), 23032308. Google ScholarDigital Library
- Kirman, B., "Get Lost, GetLostBot!" Annoying people by offering recommendations when they are not wanted. In Proc LocalPeMA'12, ACM Press (2012), 1920. Google ScholarDigital Library
- Kohonen, T., Self-organizing maps -- 3.ed., Springer, 2001 Google ScholarDigital Library
- Krüger, A., Aslan, I., Zimmer, H., The effects of mobile pedestrian navigation systems on the concurrent acquisition of route and survey knowledge. Mobile Human-Computer Interaction-- MobileHCI 2004, (2004), 39--60.Google ScholarCross Ref
- Lindqvist, J., Cranshaw, J., Wiese, J., Hong, H. and Zimmerman, J., I'm the Mayor of My House: Examining Why People Use foursquare, In Proc CHI'11, ACM Press (2011), 2409--2418. . Google ScholarDigital Library
- Pariser, E., The Filter Bubble: What the Internet is hiding from you. Penguin Press HC, 2011. Google ScholarDigital Library
- Raubal, M., Winter, S., Enriching Wayfinding Instructions with Local Landmarks, In Geographic Information Science -- Proc GIScience 2002, (2002), 243--259. Google ScholarDigital Library
- Schöning, J., Hecht, B., Starosielski, N., Evaluating automatically generated location-based stories for tourists, In Proc CHI'08, ACM Press (2008), 2937--2942. Google ScholarDigital Library
- Shang, S., Hui, P., Kulkarni, S. R., Cuff, P.W., 2012, Wisdom of the Crowd: Incorporating Social Influence in Recommendation Models. Proc. ICPADS '11, IEEE (2011), 835--840. Google ScholarDigital Library
- Turner, A., Penn, A., Encoding natural movement as an agent-based system: an investigation into human pedestrian behaviour in the built environment. 2001. Environment and Planning B: Planning and Design, 29 (2002), 473--490.Google ScholarCross Ref
Index Terms
- The path is the reward: considering social networks to contribute to the pleasure of urban strolling
Recommendations
Introducing the space recommender system: how crowd-sourced voting data can enrich urban exploration in the digital era
C&T '13: Proceedings of the 6th International Conference on Communities and TechnologiesNavigation systems like Google Maps and TomTom are designed to generate the shortest and less time consuming path for the user to reach a certain destination from his origin location, not taking into account the user's actual walking experience.
This ...
Exploring acquaintances of social network site users for effective social event recommendations
In this paper, we propose a social event recommendation method that exploits a user's social interaction relations and collaborative friendships to recommend events of interest. A challenge of the social event recommendation is that social events, such ...
Incorporating social networks and user opinions for collaborative recommendation: local trust network based method
CAMRa '10: Proceedings of the Workshop on Context-Aware Movie RecommendationThe sparse nature of historical rating profile hinders reliable similarity metrics between users, leading to poor recommendation performance. The availability of user social networks and user opinions can be incorporated to improve prediction accuracy. ...
Comments