Dynamic similarity search in multi-metric spaces
Dynamic similarity search in multi-metric spaces
复制标题
多度量空间中的动态相似性搜索
DOI：
10.1145/1178677.1178698
复制
发表时间：
2006
期刊：
影响因子：
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通讯作者：
Tomáš Skopal
中科院分区：
文献类型：
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作者：
B. Bustos;Tomáš Skopal
多媒体数据库中的一个重要研究问题是相似对象的检索。对于多媒体数据库中的大多数应用，精确的搜索是没有意义的。因此，许多努力已经致力于开发高效和有效的相似性搜索技术。最近的一种方法，已被证明可以提高多媒体数据库中的相似性搜索的有效性，诉诸于使用的组合的度量，其中每个度量的期望的贡献（权重）选择在查询时间。本文提出了多度量M树（M3树），一种度量访问方法，支持相似性查询的度量函数的动态组合。M3树是M-tree的一个扩展，它存储部分距离以更好地估计路由/地面条目与每个查询之间的加权距离，其中使用单个距离函数来构建整个索引。一个实验评估表明，M3树可能是有效的，因为有多个M树（一个为每一个）。
An important research issue in multimedia databases is the retrieval of similar objects. For most applications in multi-media 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 where the desirable contribution (weight) of each metric is chosen at query time. This paper presents the Multi-Metric M-tree (M 3 -tree), a metric access method that supports similarity queries with dynamic combinations of metric functions. The M 3-tree, an extension of the M-tree, stores partial distances to better estimate the weighed distances between routing/ground entries and each query, where a single distance function is used to build the whole index. An experimental evaluation shows that the M 3-tree may be as efficient as having multiple M-trees (one for each).