We present Grapevine, a user-controlled recommender that enables undergraduate and graduate students to find a suitable research advisor. This system combines the ideas from the areas of exploratory search, user modeling, and recommender systems by employing state-of-the-art knowledge extraction, grape-based recommendation, and an intelligent user interface. In this paper, we demonstrate the system’s key components and how they work as a whole.

The ability to perform automated conversions between data conforming to different specifications is a key ingredient to achieve interoperability among heterogeneous systemswhich, in turn, is at the basis of the creation of so-called Systems of Systems.These conversions require the definition of mappings between concepts of separate data specifications, which is typically a hard and time-consuming task.In this paper, we present a technique to automatically suggest mappings to users, based on both linguistic and structural similarities between terms.The approach has been implemented in our prototype tool, SMART (SPRINT Mapping & Annotation Recommendation Tool), and it has been validated through tests carried out using specifications from the transportation domain.