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CREF06D.tmp
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CREF06D.tmp
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%\documentclass[llncs]{svmultln}
\documentclass{llncs}
%\documentclass{article}
\usepackage{color}
\usepackage{epsfig}
\usepackage{graphicx}
\usepackage{latexsym}
\usepackage{amssymb}
\usepackage{amstext}
\usepackage{amsmath}
\usepackage{rotating}
\usepackage{booktabs}
\usepackage{subcaption}
\captionsetup{compatibility=false}
\usepackage{float}
\usepackage{array}
\usepackage{xspace}
\usepackage{paralist}
\usepackage{todonotes}
\usepackage{comment}
%\usepackage{newtxtext}
\usepackage[]{algorithm2e}
\pagestyle{plain}
\usepackage{url}
\usepackage{numprint}
\usepackage{booktabs} % nice looking tables
\usepackage{siunitx}
%\usepackage[boldmath]{numprint}
\begin{document}
\mainmatter
\title{Predictive Business Process Monitoring enhanced with Background Knowledge}
\author{Anton Yeshchenko\inst{1}\and Chiara Di Francescomarino\inst{2} \and Chiara Ghidini\inst{2} \and Fabrizio Maria Maggi\inst{1} \and Giulio Petrucci\inst{1}}
\institute{University of Tartu, Ulikooli 18, 50090 Tartu, Estonia
\email{}
\and
FBK-IRST, Via Sommarive 18, 38050 Trento, Italy
\email{}
}
\maketitle
\begin{abstract}
\input{abstract}
\end{abstract}
\keywords{Predictive Process Monitoring, Deep learning, Recurrent Neural Networks, Linear Temporal Logic}
\input{introduction}
\input{relatedwork}
\input{problem}
\input{approach}
\input{evaluation}
\input{conclusions}
\bibliographystyle{splncs03}
\bibliography{bibliography}
\end{document}