The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
WSRec: A Collaborative Filtering Based Web Service Recommender System
Abstract
As the abundance of Web services on the World Wide Web increase, designing effective approaches for Web service selection and recommendation has become more and more important. In this paper, we present WSRec, a Web service recommender system, to attack this crucial problem. WSRec includes a user-contribution mechanism for Web service QoS information collection and an effective and novel hybrid collaborative filtering algorithm for Web service QoS value prediction. WSRec is implemented by Java language and deployed to the real-world environment. To study the prediction performance, a total of 21,197 public Web services are obtained from the Internet and a large-scale real-world experiment is conducted, where more than 1.5 millions test results are collected from 150 service users in different countries on 100 publicly available Web services located all over the world. The comprehensive experimental analysis shows that WSRec achieves better prediction accuracy than other approaches.
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Cites
Item-based collaborative filtering recommendation algorithms
Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001) · Proceedings of the 10th international conference on World Wide Web · doi:10.1145/371920.372071 · Cited by 9,135
GroupLens: an open architecture for collaborative filtering of netnews
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., & Riedl, J. (1994) · Proceedings of the 1994 ACM conference on Computer supported cooperative work - CSCW '94 · doi:10.1145/192844.192905 · Cited by 5,058
Empirical Analysis of Predictive Algorithms for Collaborative Filtering
Breese, J. S., Heckerman, D. E., & Kadie, C. M. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1301.7363 · Cited by 4,772
QoS-aware middleware for Web services composition
Zeng, L., Benatallah, B., Ngu, A. H. H., Dumas, M., Kalagnanam, J., & Chang, H. (2004) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2004.11 · Cited by 2,757
Item-based top-N recommendation algorithms
Deshpande, M., & Karypis, G. (2004) · ACM Transactions on Information Systems · doi:10.1145/963770.963776 · Cited by 2,164
PlanetLab: an overlay testbed for broad-coverage services
Chun, B., Culler, D., Roscoe, T., Bavier, A., Peterson, L., Wawrzoniak, M., & Bowman, M. (2003) · ACM SIGCOMM Computer Communication Review · doi:10.1145/956993.956995 · Cited by 1,031
Personalized QoS Prediction forWeb Services via Collaborative Filtering
Shao, L., Zhang, J., Wei, Y., Zhao, J., Xie, B., & Mei, H. (2007) · IEEE International Conference on Web Services (ICWS 2007) · doi:10.1109/icws.2007.140 · Cited by 463
Effective missing data prediction for collaborative filtering
Ma, H., King, I., & Lyu, M. R.-T. (2007) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/1277741.1277751 · Cited by 427
Self-citationA collaborative filtering algorithm and evaluation metric that accurately model the user experience
McLaughlin, M. R., & Herlocker, J. L. (2004) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/1008992.1009050 · Cited by 345
Modeling User Rating Profiles For Collaborative Filtering
Marlin, B. M. (2003) · Cited by 265
Cited by
Privacy Preserving Location-Aware Personalized Web Service Recommendations
Badsha, S., Yi, X., Khalil, I., Liu, D., Nepal, S., Bertino, E., & Lam, K. Y. (2021) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2018.2839587 · Cited by 56
Metadata
- Authors
- Zheng, Z., Ma, H., Lyu, M. R., & King, I.
- Venue
- 2009 IEEE International Conference on Web Services
- Publisher
- IEEE
- Published
- 2009-07
- Pages
- 437-444
- OpenAlex
- W2123476762
- Cited by
- 448
- References
- 13
- FWCI
- 15.44
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Zheng, Z., Ma, H., Lyu, M. R., & King, I. (2009). WSRec: A Collaborative Filtering Based Web Service Recommender System. 2009 IEEE International Conference on Web Services. https://doi.org/10.1109/icws.2009.30
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