Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Analysis of Large-scale Traffic Dynamics using Non-negative Tensor
  Factorization   In this paper, we present our work on clustering and prediction of temporal
dynamics of global congestion configurations in large-scale road networks.
Instead of looking into temporal traffic state variation of individual links,
or of small areas, we focus on spatial congestion configurations of the whole
network. In our work, we aim at describing the typical temporal dynamic
patterns of this network-level traffic state and achieving long-term prediction
of the large-scale traffic dynamics, in a unified data-mining framework. To
this end, we formulate this joint task using Non-negative Tensor Factorization
(NTF), which has been shown to be a useful decomposition tools for multivariate
data sequences. Clustering and prediction are performed based on the compact
tensor factorization results. Experiments on large-scale simulated data
illustrate the interest of our method with promising results for long-term
forecast of traffic evolution.

24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th