Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Map Matching Algorithm for Large-scale Datasets   GPS receivers embedded in cell phones and connected vehicles generate a
series of location measurements that can be used for various analytical
purposes. A common pre-processing step of this data is the so-called map
matching. The goal of map matching is to infer the trajectory that the device
followed in a road network from a potentially sparse series of noisy location
measurements. Although accurate and robust map matching algorithms based on
probabilistic models exist, they are computationally heavy and thus impractical
for processing of large datasets. In this paper, we present a scalable
map-matching algorithm based on Dijkstra shortest path method, that is both
accurate and applicable to large datasets. Our experiments on a
publicly-available dataset showed that the proposed method achieves accuracy
that is comparable to that of the existing map matching methods using only a
fraction of computational resources. In result, our algorithm can be used to
efficiently process large datasets of noisy and potentially sparse location
data that would be unexploitable using existing techniques due to their high
computational requirements.

33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas