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- Paolo Ciaccia, Marco Patella, Pavel Zezula
- VLDB
- 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 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)

- Ilaria Bartolini, Paolo Ciaccia, Marco Patella
- ACM Trans. Database Syst.
- 2008

Skyline queries compute the set of Pareto-optimal tuples in a relation, that is, 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 necessitate the relation to have been indexed or have to perform the dominance tests on… (More)

- Ilaria Bartolini, Paolo Ciaccia, Marco Patella
- IEEE Transactions on Pattern Analysis and Machine…
- 2005

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. We propose a novel Fourier-based approach, called WARP, for matching and retrieving similar shapes. The unique characteristics of WARP are the exploitation… (More)

- Ilaria Bartolini, Paolo Ciaccia, Marco Patella
- CIKM
- 2006

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)

- Paolo Ciaccia, Marco Patella
- ICDE
- 2000

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

- Paolo Ciaccia, Marco Patella
- ACM Trans. Database Syst.
- 2002

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)

- Stefania Ardizzoni, Ilaria Bartolini, Marco Patella
- DEXA Workshop
- 1999

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 is… (More)

The M-tree is a dynamic paged structure that can be effectively used to index multimedia databases, where objects are represented by means of complex features and similarity queries require the computation of time-consuming distance functions. The initial loading of the M-tree, however, can be very expensive. In this paper we propose a fast (bulk) loading… (More)

- Paolo Ciaccia, DEIS CSITE, Marco Patella, Pavel Zezula
- 1997

A new access method called M tree is pro posed to organize and search large data sets from a generic metric space i e where ob ject proximity is only de ned 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 balanced… (More)

- Paolo Ciaccia, Marco Patella, Pavel Zezula
- PODS
- 1998

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 specific 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)