Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Publication date | 13/08/2015 |
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Host publication | Proceedings - 2015 IEEE International Conference on Web Services, ICWS 2015 |
Editors | Hong Zhu, John A. Miller |
Publisher | IEEE |
Pages | 217-224 |
Number of pages | 8 |
ISBN (electronic) | 9781467372725 |
<mark>Original language</mark> | English |
Event | IEEE International Conference on Web Services, ICWS 2015 - New York, United States Duration: 27/06/2015 → 2/07/2015 |
Conference | IEEE International Conference on Web Services, ICWS 2015 |
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Country/Territory | United States |
City | New York |
Period | 27/06/15 → 2/07/15 |
Conference | IEEE International Conference on Web Services, ICWS 2015 |
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Country/Territory | United States |
City | New York |
Period | 27/06/15 → 2/07/15 |
In this paper, we explore service recommendation and selection in the reusable composition context. The goal is to aid developers finding the most appropriate services in their composition tasks. We specifically focus on mashups, a domain that increasingly targets people without sophisticated programming knowledge. We propose a probabilistic matrix factorization approach with implicit correlation regularization to solve this problem. In particular, we advocate that the co-invocation of services in mashups is driven by both explicit textual similarity and implicit correlation of services, and therefore develop a latent variable model to uncover the latent connections between services by analyzing their co-invocation patterns. We crawled a real dataset from Programmable Web, and extensively evaluated the effectiveness of our proposed approach.