Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data Mining and Visualization to Understand Accident-prone Areas   In this study, we present both data mining and information visualization
techniques to identify accident-prone areas, most accident-prone time, day, and
month. Also, we surveyed among volunteers to understand which visualization
techniques help non-expert users to understand the findings better. Findings of
this study suggest that most accidents occur in the dusk (i.e., between 6 to 7
pm), and on Fridays. Results also suggest that most accidents occurred in
October, which is a popular month for tourism. These findings are consistent
with social information and can help policymakers, residents, tourists, and
other law enforcement agencies. This study can be extended to draw broader
implications.

4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
17
The categories of this paper are: q-fin