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Crowds replace experts: Building better location-based services using mobile social network interactions

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5 Author(s)
Shankar, P. ; Dept. of Comput. Sci., Rutgers Univ., Piscataway, NJ, USA ; Yun-Wu Huang ; Castro, P. ; Nath, B.
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Location-based services are growing in popularity due to the ubiquity of smartphone users. The relevance of location-based query results is very important, especially for mobile phones with limited screen size. Location-based data frequently changes; this introduces challenges in indexing and ranking places. The growing popularity of mobile social networks, such as Twitter, FourSquare and Facebook Places, presents an opportunity to build better location-based services by leveraging user interactions on these networks. In this paper, we present SocialTelescope, a location-based service that automatically compiles, indexes and ranks locations, based on user interactions with locations in mobile social networks. We implemented our system as a location-based search engine that uses geo-tweets by Twitter users to learn about places. We evaluated the coverage and relevance of our system by comparing it against current state-of-the-art approaches including page-rank (Google Local Search), expert-based (Zagat) and user-review based (Yelp). Our results show that a crowd-sourced location-based service returns results that match those returned by current approaches in relevance, at a substantially lower cost.

Published in:

Pervasive Computing and Communications (PerCom), 2012 IEEE International Conference on

Date of Conference:

19-23 March 2012

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