Applying Recommendation Systems for Composing Dynamic Services for Mobile Devices
In the context of mobile devices, services from several devices can be composed. Such compassable services may include data and device resources, such as microphones or cameras. The services can be composed to create collaborative composite services, such as video streaming. The mobility of the devices makes the service compositions inherently dynamic. Further, the set of possible service compositions may be large, and thus finding a suitable service composition at runtime becomes a challenge. Recommender systems are intelligent information systems that propose items to a user based on the user preferences, they are particularly useful in under-constrained problems, where the most suitable item is recommended from a large set of possible items that satisfy the user preferences. The main contribution of this paper is the application of knowledge-based recommendation techniques for composing dynamic services for mobile devices. The contribution is exemplified and validated with the Social Device Platform, which provides interactive, proximity-based service compositions for mobile devices. Knowledge-based recommender systems were found to be applicable technologically and feasible in terms of performance for composing dynamic services in environments where runtime composition is necessary.