Since, most of the organizations present their services electronically, the number of functionally-equivalent web services is increasing as well as the number of users that employ those web services. Consequently, plenty of information is generated by the users and the web services that lead to the users be in trouble in finding their appropriate web services. Therefore, it is required to provi...

The number of services on the Internet is growing rapidly. Thus, the problem of selecting proper services for most users becomes serious and service recommendation is widely needed. Besides functions, QoS information is also an important factor to be considered when making recommendations to users. However, QoS changes with time. To address and solve these challenges, this paper proposes a temp...

Mobile edge computing is an emerging technology that provides services within the close proximity of mobile subscribers by edge servers that are deployed in each edge server. Mobile edge computing platform enables application developers and content providers to serve context-aware services (such as service recommendation) by using real time radio access network information. In service recommend...

QoS-based web service recommendation is an important technique to select suitable services to users. In this paper, we aim to achieve superior recommendation accuracy by leveraging the known QoS records. To achieve this goal, we employ the clustering algorithm and Matrix Factorisation model (MF), and propose a collaborative framework of web service recommendation. Using the clustering algorithm...

Service recommendation has become a hot fundamental research topic in service computing. With the increasing number of services, QoS is becoming more and more important for describing non-functional characteristics of services. The most popular technique is the Collaborative Filtering (CF) based on QoS values. Existing few approaches for service recommendation based on CF have been studied, so ...

Some of the software components that are designed to support interoperable peer to peer interaction over a network are the web services. With the proliferation of web services, QoS based approach is becoming more important to service recommendation (SR). the present SR performance is not satisfactory. This is because of two reasons. First approach fails to consider the QoS variance based on use...

The number of web services with similar functionality increases which makes the service users depend on web service recommendation systems. During these days it was found that the service users pay more attention on the non-functional properties which are also known as Quality Of Service (QoS) in selecting a best Web Service. Collaborative filtering methods are used in predicting the QoS values...

Collaborative Filtering (CF) is widely employed for making Web service recommendation. CF-based Web service recommendation aims to predict missing QoS (Quality-of-Service) values of Web services. Although several CF-based Web service QoS prediction methods have been proposed in recent years, the performance still needs significant improvement. Firstly, existing QoS prediction methods seldom con...