Name
Abstract | ||
|---|---|---|
The number of online service providers and services hosted by them is rapidly increasing. Since services hosted by different service providers may have the same functionality, it is extremely hard for a user to determine those services that best match their requirements. To ease this difficulty, it is necessary that the service providing system rank those services based on users preferences, so that users receive only those services that suit them best. In this paper, a novel vector-based algorithm, which is multi-featured, semantic-based, and user-centric, is proposed for this service ranking problem. This algorithm overcomes all restrictions and limitations that exist in previously known vector-based ranking algorithms. The algorithm has been analyzed thoroughly with respect to performance, accuracy, and algorithmic complexity. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s11761-016-0200-y | Service Oriented Computing and Applications |
Keywords | Field | DocType |
Service-oriented system, User-centric preferences, Semantics, Fair ranking, Ranking algorithm | Learning to rank,Ranking,Computer science,Algorithm,Service provider,Ranking (information retrieval),Extremely hard,Algorithmic complexity,Database,Semantics,User-centered design | Journal |
Volume | Issue | ISSN |
11 | 1 | 1863-2394 |
Citations | PageRank | References |
1 | 0.36 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ammar Alsaig | 1 | 2 | 3.12 |
| Vangalur S. Alagar | 2 | 164 | 39.10 |
| Mubarak Mohammad | 3 | 118 | 10.64 |
| Wadee Alhalabi | 4 | 113 | 10.82 |