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A new access method, called M-tree, is proposed to organize and search large data sets from a generic " metric space " , i.e. where object proximity is only defined by a distance function satisfying the positivity, symmetry, and triangle inequality postulates. We detail algorithms for insertion of objects and split management, which keep the M-tree always… (More)

- Paolo Ciaccia, Marco Patella, Pavel Zezula
- 1997

A new access method, called M-tree, is proposed to organize and search large data sets from a generic \metric space", i.e. where object proximity is only deened by a distance function satisfying the positivity, symmetry, and triangle inequality postulates. We detail algorithms for insertion of objects and split management, which keep the M-tree always… (More)

Effective and efficient retrieval of similar shapes from large image databases is still a challenging problem in spite of the high relevance that shape information can have in describing image contents. In this paper, we propose a novel Fourier-based approach, called WARP, for matching and retrieving similar shapes. The unique characteristics of WARP are… (More)

In this paper we present WINDSURF (Wavelet-Based Indexing of Images Using Region Fragmentation), a new approach to content-based image retrieval. The method uses the wavelet transform to extract color and texture features from an image and applies a clustering technique to partition the image into a set of " homogeneous " regions. Similarity between images… (More)

Skyline queries compute the set of Pareto-optimal tuples in a relation, ie those tuples that are not <i>dominated</i> by any other tuple in the same relation. Although several algorithms have been proposed for efficiently evaluating skyline queries, they either require to extend the relational server with specialized access methods (which is not always… (More)

In high-dimensional and complex metric spaces, determining the nearest neighbor (NN) of a query object Õ can be a very expensive task, because of the poor partitioning operated by index structures – the so-called " curse of dimen-sionality ". This also affects approximately correct (AC) algorithms, which return as result a point whose distance from Õ is… (More)

We consider the problem of estimating CPU (distance computations) and I/O costs for processing range and k-nearest neighbors queries over metric spaces. Unlike the speciic case of vector spaces, where information on data distribution has been exploited to derive cost models for predicting the performance of multi-dimensional access methods, in a generic… (More)

Novel database applications, such as multimedia, data mining, e-commerce, and many others, make intensive use of similarity queries in order to retrieve the objects that better fit a user request. Since the effectiveness of such queries improves when the user is allowed to personalize the similarity criterion according to which database objects are… (More)

M-tree is a dynamic access method suitable to index generic " metric spaces " , where the function used to compute the distance between any two objects satisfies the positivity, symmetry, and triangle inequality postulates. The M-tree design fulfills typical requirements of multimedia applications, where objects are indexed using complex features , and… (More)

Motivated by the needs for efficient similarity retrieval in multimedia digital libraries, we present basic principles of a new paged and balanced index structure, the M ¾-tree. The M ¾-tree can be applied whenever " complex " range and/or best matches queries over different descriptions (features) of objects need to be solved. The proposed approach… (More)