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A large volume of mobile data is being generated and shared among mobile devices such as smartphones. Most of the mobile platforms provide a user with a keyword-based full text search (FTS) in order to search for mobile data. However, FTS only returns the data corresponding to the keywords given by users as results without considering a user’s query intention. To overcome this limitation, we propose a semantically enhanced keyword-based search method. Although there are various semantic search techniques, it is hard to apply existing methods to mobile devices just as they are. This is caused by 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. Experimental results from the prototype implementation of the proposed method show that the proposed method provides a better user experience than the conventional FTS and returns accurate search results in an acceptable response time.

This paper proposes a mobile search engine for smart devices, which effectively augments the result of local semantic search with useful Web information according to the intent and context of a mobile user. To support an intuitive query, we employ the conventional natural language user interface, which supports voice recognition. Through the prototype implementation of the proposed search engine, we find that it provides more meaningful search results semantically and contextually, compared with the conventional keyword-based search engines of mobile devices.