Abstract
Personalization, which has the ultimate goal of satisfying user's requests, can be perceived in terms of QoS measurement. As one of the means for the success of Semantics Web, many techniques have been effectively used in modeling and developing web service personalization. However, most of these methodologies relied heavily on detailed implicit and explicit information supply by users during initial and subsequent interactions with the systems. We propose in this paper a novel approach using the supply chain management (SCM) technique in personalizing web services as against the conventional notion of applying SCM only to product manufacturing. Our user-model based framework uses multi-agent system (MAS) components in taking requests from users and working towards their satisfaction including seeking for additional information outside the system as the need arises. Only basic stereotype information furnished by potential users at initial contact is required for personalization during subsequent interactions with the system. The system is adaptive and aimed at high quality autonomous information services where users are successfully presented preferred web services with minimum information request.
| Original language | English |
|---|---|
| Title of host publication | 2008 4th International IEEE Conference Intelligent Systems, IS 2008 |
| Pages | 1917-1922 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | 2008 4th International IEEE Conference Intelligent Systems, IS 2008 - Varna, Bulgaria Duration: 6 Sep 2008 → 8 Sep 2008 |
Publication series
| Name | 2008 4th International IEEE Conference Intelligent Systems, IS 2008 |
|---|---|
| Volume | 2 |
Conference
| Conference | 2008 4th International IEEE Conference Intelligent Systems, IS 2008 |
|---|---|
| Country/Territory | Bulgaria |
| City | Varna |
| Period | 6/09/08 → 8/09/08 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Multi-agent system
- Semantic web
- Supply chain optimization
- User modeling
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