An interactive and context-driven approach to mobile decision support services
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This thesis introduces a new approach to service sophistication where the users with no prior knowledge about a public domain's list of services can conveniently and e ectively use those services in companion with complementary utility services. Such a decision support service utilizes techniques from semantic analysis that are orchestrated through a new concept namely "Smart Decision Service" that coaches the user, who is not familiar with an organization, to select the desired organization's business services and seamlessly connect them with the proper third-party applications (e.g., map, search engine, calendar, email, voice, video) in the user's mobile device (smart phone or tablet). Such smart decision services can be provided for a variety of strategic business domains such as: banking, insurance, government, healthcare, and on-line shopping. A prototype of the application has been developed using Xcode IDE which runs on Apple iPhone. In the proposed approach the user installs a new type of agent in his/her mobile device and requests to be advised for services that a particular organization (e.g., City- bank) provides. The cloud provider sends the City-bank smart service to serve the user, which collects the context of the user and interacts with the cloud provider to select a speci c business service (e.g., stock invest) for the customer. Also the agent in the local cellphone uses the tables of maximal associations of previous customers which share the same set of conditions to recommend the current user with the services that probably meet his/her circumstances.