6,199 research outputs found
Indexing Metric Spaces for Exact Similarity Search
With the continued digitalization of societal processes, we are seeing an
explosion in available data. This is referred to as big data. In a research
setting, three aspects of the data are often viewed as the main sources of
challenges when attempting to enable value creation from big data: volume,
velocity and variety. Many studies address volume or velocity, while much fewer
studies concern the variety. Metric space is ideal for addressing variety
because it can accommodate any type of data as long as its associated distance
notion satisfies the triangle inequality. To accelerate search in metric space,
a collection of indexing techniques for metric data have been proposed.
However, existing surveys each offers only a narrow coverage, and no
comprehensive empirical study of those techniques exists. We offer a survey of
all the existing metric indexes that can support exact similarity search, by i)
summarizing all the existing partitioning, pruning and validation techniques
used for metric indexes, ii) providing the time and storage complexity analysis
on the index construction, and iii) report on a comprehensive empirical
comparison of their similarity query processing performance. Here, empirical
comparisons are used to evaluate the index performance during search as it is
hard to see the complexity analysis differences on the similarity query
processing and the query performance depends on the pruning and validation
abilities related to the data distribution. This article aims at revealing
different strengths and weaknesses of different indexing techniques in order to
offer guidance on selecting an appropriate indexing technique for a given
setting, and directing the future research for metric indexes
Transport on river networks: A dynamical approach
This study is motivated by problems related to environmental transport on
river networks. We establish statistical properties of a flow along a directed
branching network and suggest its compact parameterization. The downstream
network transport is treated as a particular case of nearest-neighbor
hierarchical aggregation with respect to the metric induced by the branching
structure of the river network. We describe the static geometric structure of a
drainage network by a tree, referred to as the static tree, and introduce an
associated dynamic tree that describes the transport along the static tree. It
is well known that the static branching structure of river networks can be
described by self-similar trees (SSTs); we demonstrate that the corresponding
dynamic trees are also self-similar. We report an unexpected phase transition
in the dynamics of three river networks, one from California and two from
Italy, demonstrate the universal features of this transition, and seek to
interpret it in hydrological terms.Comment: 38 pages, 15 figure
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