Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Time and Activity Sequence Prediction of Business Process Instances   The ability to know in advance the trend of running process instances, with
respect to different features, such as the expected completion time, would
allow business managers to timely counteract to undesired situations, in order
to prevent losses. Therefore, the ability to accurately predict future features
of running business process instances would be a very helpful aid when managing
processes, especially under service level agreement constraints. However,
making such accurate forecasts is not easy: many factors may influence the
predicted features.
  Many approaches have been proposed to cope with this problem but all of them
assume that the underling process is stationary. However, in real cases this
assumption is not always true. In this work we present new methods for
predicting the remaining time of running cases. In particular we propose a
method, assuming process stationarity, which outperforms the state-of-the-art
and two other methods which are able to make predictions even with
non-stationary processes. We also describe an approach able to predict the full
sequence of activities that a running case is going to take. All these methods
are extensively evaluated on two real case studies.

10
The categories of this paper are: q-bio
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an