Web mashup is becoming more and more popular for both general and enterprise purposes in order to implement applications that leverage on third party components. However, developing a mashup requires specialized knowledge about Web APIs, their technologies and the way to combine them in a meaningful way. For this problem, we describe in this paper an approach for searching experts in the context of enterprise mashup development and in particular, we describe how to implement typical expert search patterns. The approach is based on the integration of knowledge both internal and external to the enterprise and represented as a linked data.
Linked Data based Expert Search and Collaboration for Mashup
BIANCHINI, Devis;DE ANTONELLIS, Valeria;MELCHIORI, Michele
2013-01-01
Abstract
Web mashup is becoming more and more popular for both general and enterprise purposes in order to implement applications that leverage on third party components. However, developing a mashup requires specialized knowledge about Web APIs, their technologies and the way to combine them in a meaningful way. For this problem, we describe in this paper an approach for searching experts in the context of enterprise mashup development and in particular, we describe how to implement typical expert search patterns. The approach is based on the integration of knowledge both internal and external to the enterprise and represented as a linked data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.