The purpose of this study is to develop Linked Open Data (LOD) for social problems sustainably, and to support social problem solving by raising social awareness for the problems. In this paper, we focus on illegally parked bicycles as an example. First, we extracted information on the problem factors and designed LOD schema of the illegally parked bicycles. Then, we collected pieces of data from SNS and websites of municipalities, and built the illegally parked bicycles LOD. We also estimated missing data in the LOD using Bayesian Networks. As a result, we estimated the unknown number of the illegally parked bicycles with 72.6% accuracy. Finally, we published the enriched LOD, and then visualizes the distribution of the illegally parked bicycles on a map. We hope this leads to raise social attention on this issue.
CITATION STYLE
Egami, S., Kawamura, T., Sei, Y., Tahara, Y., & Ohsuga, A. (2016). Proposal of eco-cycle for solving illegally parked bicycles using linked open data. Transactions of the Japanese Society for Artificial Intelligence, 31(6), 1–12. https://doi.org/10.1527/tjsai.AI30-K
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