Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Learning for Predictive Business Process Monitoring: Review and
  Benchmark   Predictive monitoring of business processes is concerned with the prediction
of ongoing cases on a business process. Lately, the popularity of deep learning
techniques has propitiated an ever-growing set of approaches focused on
predictive monitoring based on these techniques. However, the high disparity of
process logs and experimental setups used to evaluate these approaches makes it
especially difficult to make a fair comparison. Furthermore, it also difficults
the selection of the most suitable approach to solve a specific problem. In
this paper, we provide both a systematic literature review of approaches that
use deep learning to tackle the predictive monitoring tasks. In addition, we
performed an exhaustive experimental evaluation of 10 different approaches over
12 publicly available process logs.

5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg