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In multimedia systems we usually need to retrieve database (DB) objects based on their similarity to a query object, while the similarity assessment is provided by a measure which defines a (dis)similarity score for every pair of DB objects. In most existing applications, the similarity measure is required to be a metric, where the triangle inequality is… (More)

- Tomás Skopal
- EDBT
- 2006

The retrieval of objects from a multimedia database employs a measure which defines a similarity score for every pair of objects. The measure should effectively follow the nature of similarity, hence, it should not be limited by the triangular inequality, regarded as a restriction in similarity modeling. On the other hand, the retrieval should be as… (More)

In this paper pivoting M-tree (PM-tree) is introduced, a metric access method combining M-tree with the pivot-based approach. While in M-tree a metric region is represented by a hyper-sphere, in PM-tree the shape of a metric region is determined as an intersection of the hyper-sphere and a set of hyper-rings. The set of hyper-rings for each metric region is… (More)

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… (More)

The M-tree is a dynamic data structure designed to index metric datasets. In this paper we introduce two dynamic techniques of building the M-tree. The first one incorporates a multi-way object insertion while the second one exploits the generalized slim-down algorithm. Usage of these techniques or even combination of them significantly increases the… (More)

We introduce a method of searching the k nearest neighbours (k-NN) using PM-tree. The PM-tree is a metric access method for similarity search in large multimedia databases. As an extension of M-tree, the structure of PM-tree exploits local dynamic pivots (like M-tree does it) as well as global static pivots (used by LAESA-like methods). While in M-tree a… (More)

In this paper we introduce the Pivoting M-tree (PM-tree), a metric access method combining M-tree with the pivot-based approach. While in M-tree a metric region is represented by a hyper-sphere, in PM-tree the shape of a metric region is determined by intersection of the hyper-sphere and a set of hyper-rings. The set of hyper-rings for each metric region is… (More)

In this paper we introduce a new M-tree building method, utilizing the classic idea of forced reinsertions. In case a leaf is about to split, some distant objects are removed from the leaf (reducing the covering radius), and then again inserted into the M-tree in a usual way. A regular leaf split is performed only after a series of unsuccessful reinsertion… (More)

The task of similarity search is widely used in various areas of computing, including multimedia databases, data mining, bioinformatics, social networks, etc. In fact, retrieval of semantically unstructured data entities requires a form of aggregated qualification that selects entities relevant to a query. A popular type of such a mechanism is similarity… (More)