e-Infrastructure and e-Services for Developing Countries. 10th EAI International Conference, AFRICOMM 2018, Dakar, Senegal, November 29-30, 2019, Proceedings

Research Article

Multi Agent-Based Addresses Geocoding for More Efficient Home Delivery Service in Developing Countries

  • @INPROCEEDINGS{10.1007/978-3-030-16042-5_26,
        author={Al Kebe and Roger Faye and Claude Lishou},
        title={Multi Agent-Based Addresses Geocoding for More Efficient Home Delivery Service in Developing Countries},
        proceedings={e-Infrastructure and e-Services for Developing Countries. 10th EAI International Conference, AFRICOMM 2018, Dakar, Senegal, November 29-30, 2019, Proceedings},
        proceedings_a={AFRICOMM},
        year={2019},
        month={3},
        keywords={Geocoding Multi agent Text mining Knowledge discovery Address standard},
        doi={10.1007/978-3-030-16042-5_26}
    }
    
  • Al Kebe
    Roger Faye
    Claude Lishou
    Year: 2019
    Multi Agent-Based Addresses Geocoding for More Efficient Home Delivery Service in Developing Countries
    AFRICOMM
    Springer
    DOI: 10.1007/978-3-030-16042-5_26
Al Kebe1,*, Roger Faye2, Claude Lishou1
  • 1: Universite Cheikh Anta Diop
  • 2: Université Amadou Mahtar MBOW
*Contact email: manskebe@gmail.com

Abstract

In this study, we present an original method that enhance geocoding system in poorly mapped areas thanks to multi-agent system. In contrast with industrialized countries, many developing countries lack formal postal address systems assignments and usage, making the operation of translating text-based addresses to absolute spatial coordinates, known as geocoding, a big challenge. We recreated a standard of address as it is perceived and used by local people, a kind of non-official national address standard since there is no official one in these areas. Then, we designed a multi agent system in which agents are assigned different tasks of geocoding process and can perform negotiation to achieve global objective: find the best possible match or approximation of a location based on current knowledge. A verification of the usefulness of the proposed approach is made in comparison with Google geocoding API which shows that the proposed approach has great potential to geocode addresses considering local context semantic issues.