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Published in:
2009 | OriginalPaper | Chapter
A Framework for Automatizing and Optimizing the Selection of Indexing Algorithms
Authors : Mihaela Brut, Sébastien Laborie, Ana-Maria Manzat, Florence Sèdes
Published in: Metadata and Semantic Research
Publisher: Springer Berlin Heidelberg
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Inside an information system, the indexation process facilitates the retrieval of specific contents. However, this process is known as time and resource consuming. Simultaneously, the diversity of multimedia indexing algorithms is growing steeply which makes harder to select the best ones for particular user needs. In this article, we propose a generic framework which determines the most suitable indexing algorithms according to user queries, hence optimizing the indexation process. In this framework, the multimedia features are used to define multimedia metadata, user queries as well as indexing algorithm descriptions. The main idea is that, apart from retrieving contents, user queries could be also used to identify a relevant set of algorithms which detect the requested features. The application of our proposed framework is illustrated through the case of an RDF-based information system. In this case, our approach could be further optimized by a broader integration of Semantic Web technologies.