Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Discretization of Temporal Data: A Survey   In real world, the huge amount of temporal data is to be processed in many
application areas such as scientific, financial, network monitoring, sensor
data analysis. Data mining techniques are primarily oriented to handle discrete
features. In the case of temporal data the time plays an important role on the
characteristics of data. To consider this effect, the data discretization
techniques have to consider the time while processing to resolve the issue by
finding the intervals of data which are more concise and precise with respect
to time. Here, this research is reviewing different data discretization
techniques used in temporal data applications according to the inclusion or
exclusion of: class label, temporal order of the data and handling of stream
data to open the research direction for temporal data discretization to improve
the performance of data mining technique.

12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph