A context-aware preference model for database querying in an Ambient Intelligent environment
| Autor: | Ling Feng, Peter M. G. Apers, Arthur H. van Bunningen |
|---|---|
| Přispěvatelé: | Databases (Former) |
| Rok vydání: | 2006 |
| Předmět: |
Ubiquitous computing
Database Relational database business.industry Computer science METIS-238713 Database schema Context (language use) Information needs computer.software_genre Expert system Personalization Description logic Knowledge base Human–computer interaction EWI-8170 Intelligent environment Sargable IR-63694 business computer |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783540378716 DEXA Proceedings of the 17th International Conference on Database and Expert Systems Applications (DEXA 2006), 33-43 STARTPAGE=33;ENDPAGE=43;TITLE=Proceedings of the 17th International Conference on Database and Expert Systems Applications (DEXA 2006) |
| ISSN: | 0302-9743 |
| DOI: | 10.1007/11827405_4 |
| Popis: | Users' preferences have traditionally been exploited in query personalization to better serve their information needs. With the emerging ubiquitous computing technologies, users will be situated in an Ambient Intelligent (AmI) environment, where users' database access will not occur at a single location in a single context as in the traditional stationary desktop computing, but rather span a multitude of contexts like office, home, hotel, plane, etc. To deliver personalized query answering in this environment, the need for context-aware query preferences arises accordingly. In this paper, we propose a knowledge-based context-aware query preference model, which can cater for both \emph{pull} and \emph{push} queries. We analyze requirements and challenges that AmI poses upon such a model and discuss the interpretation of the model in the domain of relational databases. We implant the model on top of a traditional DBMS to demonstrate the applicability and feasibility of our approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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