Supporting the efficient discovery and use of Web APIs is increasingly important as their use and popularity grows. Yet, a simple task like finding potentially interesting APIs and their related documentation turns out to be hard and time consuming even when using the best resources currently available on theWeb. In this paper we describe our research towards an automatedWeb API documentation crawler and search engine. This paper presents two main contributions. First, we have devised and exploited crowdsourcing techniques to generate a curated dataset of Web APIs documentation. Second, thanks to this dataset, we have devised an engine able to automatically detect documentation pages. Our preliminary experiments have shown that we obtain an accuracy of 80% and a precision increase of 15 points over a keyword-based heuristic we have used as baseline.
|Title of host publication||Papers from the 2012 AAAI Spring Symposium|
|Subtitle of host publication||Technical Report SS-12-04|
|Place of Publication||Paolo Alto, California|
|Number of pages||6|
|Publication status||Published - 2012|