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Pedrinaci, Carlos; Liu, Dong; Lin, Chenghua and Domingue, John
(2012).
URL: http://www.aaai.org/Symposia/Spring/sss12.php
Abstract
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.
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- Item ORO ID
- 33226
- Item Type
- Conference or Workshop Item
- Project Funding Details
-
Funded Project Name Project ID Funding Body Not Set Not Set Partly funded by the EU project VPH-Share (FP7-269978) - Academic Unit or School
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Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © 2012 Association for the Advancement of Artificial Intelligence (www.aaai.org)
- Depositing User
- Kay Dave