A search service for food consumption mobile applications via Hadoop and MapReduce technology
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Many mobile applications on safe food consumption and e-health have been developed recently. Health conscious users highly regard such applications for safe food consumption, especially for avoiding offending foods and additives. However, there is the lack of a comprehensive database containing structured or unstructured data to support such applications. In this paper we propose the MSS, a healthy food consumption search service for mobile applications utilizing Hadoop(1) and MapReduce(2) (MR). The MSS may work as a process behind a mobile application to provide a search service for information on food and food additives. MSS works by the same logic as a search engine (SE); it crawls over Web sources cataloguing relevant information for eventual use in responding to queries from mobile applications. MSS design and development are highlighted in this paper through its system architecture, query understanding, its use of the Hadoop/MapReduce Environment, and action scripts. A case study helps displaying the virtues of MSS.