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A Novel Service Recommendation Approach in Mashup Creation


Authors



Abstract

With the development of service computing technologies, the online services are massive and disordered now. How to find appropriate services quickly and build a more powerful composed service according to user interests has been a research focus in recent years. Current service recommendation algorithms often directly follow the traditional recommendation framework of ecommerce, which cannot effectively assist users to complete dynamic online business construction. Therefore, a novel service recommendation approach named UISCS (User-Interest- initial Services-Correlation-successor Services) is proposed, which is designed for interactive scenario of service composition, and it mines the user implicit interests and the service correlations for service recommendation. A series of experiments are conducted on a real-world dataset crawled from the ProgrammableWeb, and the results show that as a step-by-step service recommendation approach, the UISCS approach has obviously improved the performance of some mainstream recommendation algorithms, such as LDA, ICF , SVD and graph-based TSR.


Keywords


Pages

Total Pages: 13

DOI
10.31209/2019.100000108


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Published

Online Article

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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