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User-generated services (UGSs) are the next step in the user-generated content (UGC) trend. UGSs let end users create their own personalized services using simple graphical tools, such as Microsoft Popfly or Yahoo Pipes. This work aims to design a system to automate the requirement identification and service discovery task for UGSs. The system will analyze context, user profile, and user history to find suitable services, combining semantic characterization and metrics with AI and pattern recognition algorithms, such as neural networks, to identify user requirements in real time and match them with existing services.