Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient classification of billions of points into complex geographic
  regions using hierarchical triangular mesh   We present a case study about the spatial indexing and regional
classification of billions of geographic coordinates from geo-tagged social
network data using Hierarchical Triangular Mesh (HTM) implemented for Microsoft
SQL Server. Due to the lack of certain features of the HTM library, we use it
in conjunction with the GIS functions of SQL Server to significantly increase
the efficiency of pre-filtering of spatial filter and join queries. For
example, we implemented a new algorithm to compute the HTM tessellation of
complex geographic regions and precomputed the intersections of HTM triangles
and geographic regions for faster false-positive filtering. With full control
over the index structure, HTM-based pre-filtering of simple containment
searches outperforms SQL Server spatial indices by a factor of ten and
HTM-based spatial joins run about a hundred times faster.

37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph