With the increasing number of mobile devices, there have been many researches on searching and managing a large volume of mobile data. Most of the mobile platforms today provide users with keyword-based full text search (FTS) in order to search for mobile data. Recently, voice search interfaces have been deployed. These search methods, however, query only the keywords given as an input to local databases in mobile devices. Therefore, it is quite difficult to figure out and to provide what a user really wants. To overcome this limitation, we propose a semantic search method for mobile platforms. The proposed method augments the results of semantic search on local databases with their related useful Web information according to the intention and context information of a user. Although there are various semantic search techniques, it is hard to apply the existing methods to mobile devices due to the characteristics of mobile devices such as isolated database structures and limited computing resources. To enable semantic search on mobile devices, we also propose a lightweight mobile ontology. The proposed mobile ontology is also aligned with related Web information to enrich search results. Experimental results from prototype implementation of the proposed method verify that our approach provides more accurate results than the conventional FTS does. In addition, the proposed method shows an acceptable amount of response time and battery consumption.