Title :
Knowledge Discovery in Services
Author_Institution :
Univ. of Notre Dame, Notre Dame, IN
Abstract :
Service mashups can be useful in understanding Web-scale workflows. Although creating a service mashup shares similar challenges with data integration, a more exciting aspect of this area is the ability to predict which services are viable candidates for a mashup. Such "service mashup recommendations" can enable knowledge discovery, an approach the author calls knowledge discovery in services (KDS).
Keywords :
Web services; data mining; Web-scale workflows; data integration; knowledge discovery; service mashup recommendations; Cleaning; Data mining; Filtering; Mashups; OWL; Phase noise; Unified modeling language; Web and internet services; Web services; KDS; Web-Scale Workflow; knowledge discovery and databases; service mashup; service-oriented computing;
Journal_Title :
Internet Computing, IEEE
DOI :
10.1109/MIC.2009.39
