Paper Info
Title
Predicting New Composition Relations Between Web Services Via Link Analysis
Abstract
With the wide application of service-oriented architecture (SOA) and service-oriented computing (SOC), the past decade has witnessed a rapid growth of the number of web services on the internet. Against this background, combining different web services to create new applications has attracted great interest from developers. However, according to latest statistics, only a small number of popular services are frequently used by developers and the use rates of most web services are rather low. To help service users discover appropriate web services and promote service compositions has thus become a significant need. In the following paper, we propose a link-based approach to predict new composition relations between web services. The approach is based on exploration of known composition relations and similarity relations among web services. To measure the composition or similarity degrees, several link-based methods are exploited, and two reasonable heuristic rules for integrating the existing composition and similarity relations for service composition prediction are developed. Case studies and experiments based on real web service datasets validated the proposed approach.
Year
DOI
Venue
2019
10.1504/IJCSE.2019.103256
INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING
Keywords
DocType
Volume
service composition, composition relations, similarity relations, link prediction, web services, API, Mashup
Journal
20
Issue
ISSN
Citations 
1
1742-7185
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Tang Mingdong155739.35
Fenfang Xie200.34
Wei Liang300.34
Yanmin Xia400.68
Kuan-ching Li5933122.44