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- W1805322114 abstract "Search effectiveness in an image database is always a trade-off between the indexing cost and semantic richness. A solution that provides a significant degree of semantic richness that simultaneously limits the indexing cost is presented. The query schemes are able to enhance the query speed by adopting a semantically rich structured form for high-level image content information, as well as exploiting the efficiency of conventional database search. Through the use of rules, which can be either pre-defined or dynamically incorporated, a new level of semantic richness can be established, which will eliminate the costly detailed indexing of individual concepts. The query algorithm incorporates rule-based conceptual navigation, customized weighting, incremental indexing and relevance feedback mechanisms to enhance retrieval effectiveness.KeywordsIndex TableElementary FactOutline FactQuery ProcessorSemantic RichnessThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W1805322114 date "1999-01-01" @default.
- W1805322114 modified "2023-09-27" @default.
- W1805322114 title "Automatic Index Expansion for Concept-Based Image Query" @default.
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- W1805322114 doi "https://doi.org/10.1007/3-540-48762-x_50" @default.
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