Abstract
On account of prevalence of mobile devices, a variety of mobile-based services have been conducted recently. In this situation, it is possible to serve the information that fits to users’ requests according to the users’ context using mobile devices. Therefore, it is necessary to research data mining techniques with mobile devices. Therefore, we researched information retrieval system in mobile environment. We applied semantic data mining method with context information ontology. These techniques of semantic information retrieval can provide the information according to users’ context information such as location, weather, user preference etc. exactly and rapidly anytime and anyplace. In modern society, it is essential to develop mobile information retrieval system which is efficient to users. Also, the system can provide users’ current location and the location information with Google map APIs in mobile devices. Therefore, in this paper, we researched semantic data mining technique with context information ontology using mobile techniques. And we compared and evaluated our proposed model and the existing model in three areas and showed our proposed model has higher performance.
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Funding
This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 21DCRU-B158151-01).
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Gu, M.S., Hwang, J. & Mun, HJ. Design and implementation for semantic information retrieval through convergence of ontology and user context based on mobile device. Pers Ubiquit Comput 27, 1123–1138 (2023). https://doi.org/10.1007/s00779-020-01503-2
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DOI: https://doi.org/10.1007/s00779-020-01503-2