Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Extracting Point of Interest and Classifying Environment for Low
  Sampling Crowd Sensing Smartphone Sensor Data   The advancement of smartphones with various type of sensors enabled us to
harness diverse information with crowd sensing mobile application. However,
traditional approaches have suffered drawbacks such as high battery consumption
as a trade off to obtain high accuracy data using high sampling rate. To
mitigate the battery consumption, we proposed low sampling point of interest
(POI) extraction framework, which is built upon validation based stay points
detection (VSPD) and sensor fusion based environment classification (SFEC). We
studied various of clustering algorithm and showed that density based spatial
clustering of application with noise(DBSCAN) algorithms produce most accurate
result among existing methods. The SFEC model is utilized for classifying the
indoor or outdoor environment of the POI clustered earlier by VSPD. Real world
data are collected, bench-marked using existing clustering method to denote
effectiveness of low sampling rate model in high noise spatial temporal data.

8
The categories of this paper are: hep-ex
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom