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| Title | Adapting Metric Indexes for Searching in Multi-metric Spaces |
| Authors | Benjamin Bustos, Sebastián Kreft, Tomas Skopal |
| Publication date | June 2012 |
| Abstract |
An important research issue in multimedia databases is the retrieval of similar objects. For most applications in multimedia databases, an exact search is not meaningful. Thus, much effort has been devoted to develop efficient and effective similarity search techniques. A recent approach that has been shown to improve the effectiveness of similarity search in multimedia databases resorts to the usage of combinations of metrics (i.e., a search on a multi-metric space). In this approach, the desirable contribution (weight) of each metric is chosen at query time. It follows that standard metric indexes cannot be directly used to improve the efficiency of dynamically weighted queries, because they assume that there is only one fixed distance function at indexing and query time. This paper presents a methodology for adapting metric indexes to multi-metric indexes, that is, to support similarity queries with dynamic combinations of metric functions. The adapted indexes are built with a single distance function and store partial distances to estimate the dynamically weighed distances. We present two novel indexes for multimetric space indexing, which are the result of the application of the proposed methodology. |
| Downloaded | 0 times |
| Pages | 467-496 |
| Volume | 58 |
| Journal name | Multimedia Tools and Applications |
| Publisher | Springer (New York, NY, USA) |
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