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.

由于移动设备的普及，最近已经进行了各种基于移动的服务。在这种情况下，可以使用移动设备根据用户的上下文来提供适合用户请求的信息。因此，有必要研究移动设备的数据挖掘技术。因此，我们研究了移动环境中的信息检索系统。我们将语义数据挖掘方法与上下文信息本体结合使用。这些语义信息检索技术可以随时随地准确，快速地根据用户的上下文信息提供信息，例如位置，天气，用户偏好等。在现代社会中，开发对用户有效的移动信息检索系统至关重要。也，该系统可以通过移动设备中的Google Maps API提供用户的当前位置和位置信息。因此，本文研究了利用移动技术结合上下文信息本体进行语义数据挖掘的技术。并且我们在三个方面对我们提出的模型和现有模型进行了比较和评估，表明我们提出的模型具有更高的性能。