Social interaction leverages collective intelligence through user-generated content, social networking, and social annotation. Users are enabled to enrich knowledge representation by rating, commenting, and tagging. The existing systems for service discovery make use of semantic relation among social tags, but ignore the relation between a user information need for services and tags. This paper first provides an overview of how social tagging is applied to discover contents/services. An enhanced web widget discovery model that aims to discover services mostly relevant to users is then proposed. The model includes an algorithm that quantifies the accurate relation between user intent for a service and the tags of a widget, as well as three different widget discovery schemes. Using the online service of Widgetbox.com, we experimentally demonstrate the accuracy and efficiency of our system.