The tremendous growth in the amount of available (Web) services impulses many researchers on proposing discovery, recommendation and management tools and techniques to help users retrieve services efficiently. Services can be consumed in different contexts: published in distributed registries; invoked as individual services which provide interfaces to receive inputs and return outputs; or composed and integrated into service-based processes as new value added composite services. In our work, we aim at facilitating service discovery and management in these three consumption contexts. First, we propose a functionality-driven approach by clustering and organizing registries according to the functionalities of the service they advertise. Second, to recommend services for individual use, we propose a usage-driven approach that takes into account the user usage data which reflect the user interest. Third, to recommend services for process use, we propose a composition-driven recommendation approach that takes into account the relations between services in service-based processes. We develop applications, as a proof of concept, to validate our techniques. We also perform experiments on the data collected by our applications and on large public datasets. Experimental results show that our techniques are feasible, accurate and have good performance in real use-cases