Gauss-Seidel is a popular multigrid smoother as it is provably optimal on structured grids
and exhibits superior performance on unstructured grids. Gauss-Seidel is not used to our …

Metric-space indexing abstracts various data types into universal metric spaces and prunes
data only exploiting the triangle inequality of the distance function in metric spaces. Since …

Distance-based indexing exploits only the triangle inequality to answer similarity queries in
metric spaces. Lacking coordinate structure, mathematical tools in Rn can only be applied …

Motivation: We reformulate the problem of comparing mass-spectra by map** spectra to a
vector space model. Our search method leverages a metric space indexing algorithm to …

Indexing metric spaces have long been a heated subject in the area of data processing. This
paper proposes the method to accelerate similarity images retrieval in airport video monitor …

Metric spaces, which generalise the properties of commonly-encountered physical and
abstract spaces into a mathematical framework, frequently occur in computer science …

Distance-based indexing exploits only the triangle inequality to answer similarity queries in
metric spaces. Lacking of coordinate structure, mathematical tools in Rn can only be applied …

Big data has received great attention in research and application. However, most of the
current efforts focus on system and application to handle the challenges of “volume” and …

Tree structure metric-space indexing methods recursively partition data according to their
distances to a set of selected reference points (also called pivots). There are two basic forms …

When searching databases of nucleotide or protein sequences, finding a local alignment of
two sequences is one of the main tasks. Since the sizes of available databases grow …