Data series are a special type of multidimensional data present in numerous domains,
where similarity search is a key operation that has been extensively studied in the data …

We present a new similarity search library and discuss a variety of design and performance
issues related to its development. We adopt a position that engineering is equally important …

Nearest neighbor searching of large databases in high-dimensional spaces is inherently
difficult due to the curse of dimensionality. A flavor of approximation is, therefore, necessary …

Metric space is a universal and versatile model of similarity that can be applied in various
areas of information retrieval. However, a general, efficient, and scalable solution for metric …

We survey permutation-based methods for approximate k-nearest neighbor search. In these
methods, every data point is represented by a ranked list of pivots sorted by the distance to …

We propose a new efficient and accurate technique for generic approximate similarity
searching, based on the use of inverted files. We represent each object of a dataset by the …

Surprising as it may seem, many of the early adopters of the object-oriented paradigm
already face a number of problems typically encountered in large-scale legacy systems …

Visual information retrieval (VIR) is an active and vibrant research area, which attempts at
providing means for organizing, indexing, annotating, and retrieving visual information …

Permutation-based Indexing (PBI) approaches have been proven to be particularly effective
for conducting large-scale approximate metric searching. These methods rely on the idea of …

LIRe (Lucene Image Retrieval) is an open source library for content based image retrieval.
Besides providing multiple common and state of the art retrieval mechanisms it allows for …