5th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing

Research Article

An analytical study of GWAP-based geospatial tagging systems

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        author={Ling-Jyh Chen and Yu-Song Syu and Bo-Chun Wang and Wang-Chien Lee},
        title={An analytical study of GWAP-based geospatial tagging systems},
        proceedings={5th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing},
        keywords={Algorithm design and analysis Application software Computer science Context modeling Global Positioning System Handheld computers Information analysis Information science Performance analysis Tagging},
        doi={10.4108/ICST.COLLABORATECOM2009.8322 }
  • Ling-Jyh Chen
    Yu-Song Syu
    Bo-Chun Wang
    Wang-Chien Lee
    Year: 2009
    An analytical study of GWAP-based geospatial tagging systems
    DOI: 10.4108/ICST.COLLABORATECOM2009.8322
Ling-Jyh Chen1,*, Yu-Song Syu1,*, Bo-Chun Wang1,*, Wang-Chien Lee2,*
  • 1: Institute of Information Science, Academia Sinica, Taiwan
  • 2: Department of Computer Science and Engineering, The Pennsylvania State University
*Contact email: cclljj@iis.sinica.edu.tw, yssyu@iis.sinica.edu.tw, bcwang@iis.sinica.edu.tw, wlee@cse.psu.edu


Geospatial tagging (geotagging) is an emerging and very promising application that can help users find a wide variety of location-specific information, and facilitate the development of future location-based services. Conventional geotagging systems share some limitations, such as the use of a two-phase operating model and the tendency to tag popular objects with simple contexts. To address these problems, geotagging systems based on the concept of `Games with a Purpose' (GWAP) have been developed recently. In this study, we use analysis to investigate these new systems. Based on our analysis results, we design three metrics to evaluate the system performance, and develop five task assignment algorithms for a GWAP-based system. Using a comprehensive set of simulations under both synthetic and realistic mobility scenarios, we find that the Least-Throughput-First Assignment algorithm (LTFA) is the most effective approach because it can achieve competitive system utility, while its computational complexity remains moderate. We also find that, to improve the system utility, it is better to assign as many tasks as possible in each round. However, because players may feel annoyed if too many tasks are assigned at the same time, it is recommended that multiple tasks be assigned one by one in each round in order to achieve higher system utility.