Name
Abstract | ||
|---|---|---|
Web services classification and clustering rely on discriminative representations of service functional semantics. Most existing topic-based methods for Web service representation simply leverage word co-occurrence relations, which may cause sub-optimal results for some specific-tasks due to the sparse features in the short service descriptions. Despite sparse and discrete word statistical feature... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SCC53864.2021.00015 | 2021 IEEE International Conference on Services Computing (SCC) |
Keywords | DocType | ISBN |
Web services,Conferences,Computational modeling,Semantics,Service computing,Bayes methods,Gaussian mixture model | Conference | 978-1-6654-1683-2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangping Zhang | 1 | 3 | 3.12 |
| Jianxun Liu | 2 | 640 | 67.12 |
| Min Shi | 3 | 11 | 4.31 |
| Buqing Cao | 4 | 9 | 5.93 |