Matching Based Content Discovery Method on Geo-Centric Information Platform
| Autor: | Myung J. Lee, Yuzo Taenaka, Kaoru Nagashima, Kazuya Tsukamoto, Akira Nagata, Hitomi Tamura |
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| Rok vydání: | 2020 |
| Předmět: |
050210 logistics & transportation
Matching (statistics) Information retrieval Geographic area business.industry Computer science 05 social sciences 02 engineering and technology Content discovery Sensor fusion Geolocation 0502 economics and business 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Internet of Things business |
| Zdroj: | Advances in Intelligent Networking and Collaborative Systems ISBN: 9783030577957 INCoS |
| DOI: | 10.1007/978-3-030-57796-4_45 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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