The move-split-merge metric for time series
A Stefan, V Athitsos, G Das - IEEE transactions on Knowledge …, 2012 - ieeexplore.ieee.org
A novel metric for time series, called Move-Split-Merge (MSM), is proposed. This metric uses
as building blocks three fundamental operations: Move, Split, and Merge, which can be …
as building blocks three fundamental operations: Move, Split, and Merge, which can be …
Accelerating similarity search for elastic measures: A study and new generalization of lower bounding distances
Similarity search is a core analytical task, and its performance critically depends on the
choice of distance measure. For time-series querying, elastic measures achieve state-of-the …
choice of distance measure. For time-series querying, elastic measures achieve state-of-the …
The basic principles of metric indexing
ML Hetland - Swarm intelligence for multi-objective problems in data …, 2009 - Springer
This chapter describes several methods of similarity search, based on metric indexing, in
terms of their common, underlying principles. Several approaches to creating lower bounds …
terms of their common, underlying principles. Several approaches to creating lower bounds …
Selectivity functions of range queries are learnable
This paper explores the use of machine learning for estimating the selectivity of range
queries in database systems. Using classic learning theory for real-valued functions based …
queries in database systems. Using classic learning theory for real-valued functions based …
[PDF][PDF] Heap based k-nearest neighbor search on GPUs
The k-nearest neighbor algorithm finds, for a given query, the k most similar samples from a
reference set. It has been successfully applied in a broad range of applications in the field of …
reference set. It has been successfully applied in a broad range of applications in the field of …
Scheduling metric-space queries processing on multi-core processors
This paper proposes a strategy to organize metric-space query processing in multi-core
search nodes as understood in the context of search engines running on clusters of …
search nodes as understood in the context of search engines running on clusters of …
Ptolemaic indexing
ML Hetland - arXiv preprint arXiv:0911.4384, 2009 - arxiv.org
This paper discusses a new family of bounds for use in similarity search, related to those
used in metric indexing, but based on Ptolemy's inequality, rather than the metric axioms …
used in metric indexing, but based on Ptolemy's inequality, rather than the metric axioms …
Ptolemaic indexing
ML Hetland - Journal of Computational Geometry, 2015 - jocg.org
This paper discusses a new family of bounds for use in similarity search, related to those
used in metric indexing, but based on Ptolemy's inequality, rather than the metric axioms …
used in metric indexing, but based on Ptolemy's inequality, rather than the metric axioms …
Performance modeling of heterogeneous systems
JC Meyer, AC Elster - 2010 IEEE International Symposium on …, 2010 - ieeexplore.ieee.org
Predicting how well applications may run on modern systems is becoming increasingly
challenging. It is no longer sufficient to look at number of floating point operations and …
challenging. It is no longer sufficient to look at number of floating point operations and …
Hybrid index for metric space databases
We present an index data structure for metric-space databases. The proposed method has
the advantage of allowing an efficient use of secondary memory. In the case of index entirely …
the advantage of allowing an efficient use of secondary memory. In the case of index entirely …