Abstract
A mashup is a Web application that integrates data, computation and UI elements provided by several components into a single tool. The concept originated from the understanding that there is an increasing number of applications available on the Web and a growing need to combine them in order to meet user requirements. This paper presents MatchUp, a system that supports rapid, on-demand, intuitive development of mashups, based on a novel autocompletion mechanism. The key observation guiding the development of MatchUp is that mashups developed by different users typically share common characteristics; they use similar classes of mashup components and glue them together in a similar manner. MatchUp exploits these similarities to recommend useful completions (missing components and connections between them) for a user's partial mashup specification. The user is presented with a ranking of the recommendations from which she can choose and refine according to her needs. This paper presents the data model and ranking metric underlying our novel autocompletion mechanism. It introduces an efficient top-k ranking algorithm that is at the core of the MatchUp system and that is formally proved to be optimal in some natural sense. We also experimentally demonstrate the efficiency of our algorithm and the effectiveness of our proposal for rapid mashup construction.
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