Mashups are becoming the de facto approach to build customer-oriented Web applications, by combining several Web APIs into a single lightweight, rich, customized Web front-end. To help mashup builders to choose among a plethora of available APIs to assemble in their mashups, some existing recommendation techniques rank candidate APIs using popularity (a social measure) or keyword-based measures (whether semantic or unverified tags). This article proposes to use information on co-usage of APIs in previous mash ups to suggest likely candidate APIs, and introduces a global measure which improves on earlier local co-API measures. The gCAR (global Co-utilization API Ranking) is calculated using association rules inferred from historical API usage data. The MashupRECO tool combines gCAR and a keywordbased measure, to avoid the 'cold-start' problem for new or unused APIs. Evaluation of MashupRECO versus the keyword search of the well-known ProgrammableWeb catalog show that the tool reduces the search time for comparable degree of completeness. © 2011 IEEE.
|Número de páginas||7|
|Estado||Publicada - 1 dic 2012|
|Evento||Proceedings - International Conference of the Chilean Computer Science Society, SCCC - |
Duración: 2 jul 2018 → …
|Conferencia||Proceedings - International Conference of the Chilean Computer Science Society, SCCC|
|Período||2/07/18 → …|
Tapia, B., Torres, R., Astudillo, H., & Ortega, P. (2012). Recommending APIs for mashup completion using association rules mined from real usage data. 83-89. Papel presentado en Proceedings - International Conference of the Chilean Computer Science Society, SCCC, . https://doi.org/10.1109/SCCC.2011.12