Adapting metric indexes for searching in multi-metric spaces
Adapting metric indexes for searching in multi-metric spaces
复制标题
调整度量索引以在多度量空间中进行搜索
DOI：
10.1007/s11042-011-0731-3
复制
发表时间：
2012
影响因子：
3.6
通讯作者：
Tomáš Skopal
中科院分区：
文献类型：
--
作者：
B. Bustos;Sebastian Kreft;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程序来说，精确的搜索没有意义。因此，人们一直致力于开发高效和有效的相似性搜索技术。最近已被证明可以提高多媒体数据库中相似性搜索的有效性的一种方法求助于度量的组合的使用(即，在多度量空间上的搜索)。在该方法中，在查询时选择每个指标的期望贡献(权重)。因此，标准度量索引不能直接用于提高动态加权查询的效率，因为它们假设在索引和查询时只有一个固定距离函数。提出了一种使度量索引适应多度量索引的方法，即通过度量函数的动态组合来支持相似性查询。自适应索引用单个距离函数建立，并存储部分距离以估计动态加权的距离。我们提出了两种用于多维空间索引的新索引，它们是应用所提出的方法的结果。
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.