Έξυπνη επιλογή υπηρεσιών διαδικτύου με εξασφάλιση δυναμικών χαρακτηριστικών ποιότητας QoS (Quality οf Service)
Smart web services selection utilizing dynamic Quality οf Service Characteristics

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Keywords
Recommender Systems ; KNNAbstract
This paper introduces an application designed to aid users in identifying the most suitable web service from a
collection of 365 options. This can be achieved by taking into consideration the End User’s preferences, which
are inferred from historical rating data.
The dissertation begins with a retrospective examination of the evolution of Web Services and the development
of recommendation systems. By employing the K-Nearest Neighbors (KNN) algorithm, the application effectively
groups web service consumers, thereby enhancing the accuracy of subsequent service recommendations.
The software is developed in C# and leverages a selection of NuGet packages for graph generation, operating
in conjunction with a Postgresql database backend.