Abstract
We have proposed a concept of new information platform, Geo-Centric information platform (GCIP), that enables IoT data fusion based on geolocation. GCIP produces new and dynamic contents by combining cross-domain data in each geographic area and provides them to users. In this environment, it is difficult to find appropriate contents requested by a user because the user cannot recognize what contents are created in each area beforehand. In this paper, we propose a content discovery method for GCIP. This method evaluates the relevancy between topics specified in user requests and topics representing IoT data used for creating contents, called matching, and presents the candidates for the desired contents based on the relevancy. Simulation results showed that appropriate contents can reliably be discovered in response to user’s request.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Number JP18H03234, NICT Grant Number 19304, USA Grant number 1818884, and 1827923.
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Nagashima, K., Taenaka, Y., Nagata, A., Tamura, H., Tsukamoto, K., Lee, M. (2021). Matching Based Content Discovery Method on Geo-Centric Information Platform. In: Barolli, L., Li, K., Miwa, H. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2020. Advances in Intelligent Systems and Computing, vol 1263. Springer, Cham. https://doi.org/10.1007/978-3-030-57796-4_45
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DOI: https://doi.org/10.1007/978-3-030-57796-4_45
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