IQSrec: An Efficient and Diversified Skyline Services Recommendation on Incomplete QoS

被引:7
|
作者
Shu, Yanjun [1 ]
Zhang, Jianhang [1 ]
Zhang, Wei Emma [2 ]
Zuo, Decheng [1 ]
Sheng, Quan Z. Z. [3 ]
机构
[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China
[2] Univ Adelaide, Sch Comp Sci, Adelaide 5005, Australia
[3] Macquarie Univ, Sch Comp, Sydney 2109, Australia
基金
中国国家自然科学基金;
关键词
Quality of service; Probabilistic logic; Throughput; Reliability; Web services; Computer science; Australia; Service recommendation; skyline services; quality of service; space partition;
D O I
10.1109/TSC.2022.3189503
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recent developments of Internet technologies have accelerated the growth of Web services (e.g., open APIs). As many services provide similar functionality, service recommendation systems use the Quality of Service (QoS) to help users find optimal services. Space partition attracts significant attention in service recommendation since it improves the diversity of recommendations and accelerates skyline services query. However, existing partition-based service recommendation systems are all implemented on complete QoS. They are not sufficient when some services' QoS values are missing or invalid. To this end, we develop a new partition-based service recommendation method on incomplete QoS (named IQSrec) that combines probabilistic skyline query and space partition. The probabilistic skyline query measures top-$k$k skyline services on incomplete QoS. A dimension-based partition is specially designed for splitting the incomplete QoS service space into $d$d-dimensional partitions with the most representative services. The candidate skyline services are chosen from each partition and merged together for probabilistic skyline computation. IQSrec selects the highest skyline probability services in each partition as recommendations. The experiments on the synthetic and real-world datasets show IQSrec can efficiently recommend skyline services on incomplete QoS. IQSrec has higher accuracy and diversity compared to the state-of-the-art service recommendation approaches.
引用
收藏
页码:1934 / 1948
页数:15
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