
The emergence of service-oriented computing as a key-enabler of web applications and the subsequent increase in the web services available, has brought to the surface a major disadvantage of service oriented architecture: there is no consistent way for the consumer to select services based on non-functional, quality requirements. Consumers perceive quality through the prism of their own experience and it is important to see how their evaluation of the quality provided is mapped to the specific quality parameters offered by the provider. In order to achieve that, this work suggests to use consumer ratings of the latter parameters so as to create a consumer quality profile and a provider reputation. By correlating this profile with others, it is possible to identify similarities in the service ratings that will lead to a prediction of which service might be the most appropriate for a specific consumer. Based on this rationale, we devised a Service Recommender mechanism and introduced a slight modification in the service lifecycle to accommodate the new Service Recommendation protocol that supports the mechanism.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 25 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
