• DocumentCode
    1728727
  • Title

    Walking Route Recommender System Considering SAW Criteria

  • Author

    Sasaki, Wataru ; Takama, Yasufumi

  • Author_Institution
    Grad. Sch. of Syst. Design, Tokyo Metropolitan Univ., Hino, Japan
  • fYear
    2013
  • Firstpage
    246
  • Lastpage
    251
  • Abstract
    This paper proposes a walking route recommender system considering criteria for route safety, amenity and walk ability. This paper refers to these criteria as SAW criteria. Walking is one of the easiest ways for health promotion, and a large number of people of all ages are enjoying it in various styles. As various people have different preference and health conditions, a walking rote recommender system has to provide them with a route considering various criteria, such as avoidance of steeps for elder people and existence of a coffee shop on route. However, existing route recommender systems usually employ only distance and necessary time between the current location and the specified location to make recommendations. This paper focuses on three criteria, including route safety, amenity and walk ability, and proposes a method for recommending various routes considering these SAW criteria. In order to determine a route while considering such criteria, the proposed method combines A algorithm and genetic algorithm. Another contribution of the system is to employ OSM (Open Street Map), which is converted into RDF (Resource Description Framework) and stored in SPARQL endpoint. Converting road information into RDF data makes it easy to extend database by incorporating various information about a road in future. This paper shows the proposed system is able to recommend reasonable and various routes through the simulations assuming users having various criteria and by subjective evaluation.
  • Keywords
    geographic information systems; recommender systems; social sciences computing; OSM; RDF; SAW criteria; SPARQL endpoint; coffee shop; elder people; health conditions; health promotion; open street map; resource description framework; route amenity; route safety; route walkability; steeps avoidance; walking route recommender system; Genetic algorithms; Legged locomotion; Recommender systems; Resource description framework; Roads; Safety; Surface acoustic waves; Open Street Map; RDF; recommender systems; walking route recommendation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Technologies and Applications of Artificial Intelligence (TAAI), 2013 Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4799-2528-5
  • Type

    conf

  • DOI
    10.1109/TAAI.2013.56
  • Filename
    6783875