Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multivariate Business Process Representation Learning utilizing Gramian
  Angular Fields and Convolutional Neural Networks   Learning meaningful representations of data is an important aspect of machine
learning and has recently been successfully applied to many domains like
language understanding or computer vision. Instead of training a model for one
specific task, representation learning is about training a model to capture all
useful information in the underlying data and make it accessible for a
predictor. For predictive process analytics, it is essential to have all
explanatory characteristics of a process instance available when making
predictions about the future, as well as for clustering and anomaly detection.
Due to the large variety of perspectives and types within business process
data, generating a good representation is a challenging task. In this paper, we
propose a novel approach for representation learning of business process
instances which can process and combine most perspectives in an event log. In
conjunction with a self-supervised pre-training method, we show the
capabilities of the approach through a visualization of the representation
space and case retrieval. Furthermore, the pre-trained model is fine-tuned to
multiple process prediction tasks and demonstrates its effectiveness in
comparison with existing approaches.

11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
2
The categories of this paper are: math