Personalized QoS Prediction forWeb Services via Collaborative Filtering

By Lingshuang Shao, Jing Zhang, Yong Wei, Junfeng Zhao, Bing Xie, Hong Mei. IEEE International Conference on Web Services (ICWS 2007), 2007

504 citations recorded by the source corpus.

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Investigating QoS of Real-World Web Services (2014, methodology): “A number of QoS prediction approaches have been proposed, including user-based QoS prediction approach [17], UIPCC [4], matrix factorization approach [5], ranking-oriented approach [18], RegionKNN [3], and so on.”
Temporal QoS-aware web service recommendation via non-negative tensor factorization (2014, methodology): “In [24], the authors propose a user-based CF algorithm to predict the QoS value from similar Web service users.”
Distributed QoS Evaluation for Real-World Web Services (2010, background): “In the ﬁeld of service computing [17], a number of QoS driven approaches have been engaged for service selection [8, 15], optimal service composition [2, 5, 16], fault tolerant Web services [7, 18, 19], Web service recommendation [12, 13], and so on.”
WSRec: A Collaborative Filtering Based Web Service Recommender System (2009, methodology): “Work [14] proposes a user-based PCC method for the Web service QoS value prediction, however, as shown in Section 4.”
QoS-Aware Web Service Recommendation via Collaborative Filtering (2014, methodology): “[28] use a user-based CF algorithm to predict QoS values.”