2898 2020 eng 225 230 6 conferencepaper IEEE 0 -- -- -- The analysis of ongoing processes is an important task in business process management. This is not surprising, since (e.g.) being able to predict future events in processes enables companies to intervene at an early stage if deviations from a desired workflow are likely to occur. Subsequently, errors and associated financial losses can be prevented or avoided. A common basis for being able to predict future events is a sequence of previous events that are typically stored in a socalled event log. In this work we present a neural network with attention mechanism, which is trained using publicly available event logs (e.g. BPI Challenge 2013). Furthermore, we elaborate the proposed model with an extensive dataset of events of a worldwide known German software company. In addition to promising results (e.g.) with regard to n-gram models, the training time of the proposed model is shorter than that of typical reference models such as neural networks with a long short-term memory architecture (LSTM). 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) 10.1109/ICAIIC48513.2020.9065057 true {"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T19:01:37Z","timestamp":1730228497759,"version":"3.28.0"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1109\/icaiic48513.2020.9065057","type":"proceedings-article","created":{"date-parts":[[2020,4,17]],"date-time":"2020-04-17T05:46:17Z","timestamp":1587102377000},"page":"225-230","source":"Crossref","is-referenced-by-count":15,"title":["Predictive Analysis of Business Processes Using Neural Networks with Attention Mechanism"],"prefix":"10.1109","author":[{"given":"Patrick","family":"Philipp","sequence":"first","affiliation":[{"name":"Vision and Fusion Laboratory IES, Karlsruhe Institute of Technology KIT,Karlsruhe,Germany"}]},{"given":"Ruben","family":"Jacob","sequence":"additional","affiliation":[{"name":"Vision and Fusion Laboratory IES, Karlsruhe Institute of Technology KIT,Karlsruhe,Germany"}]},{"given":"Sebastian","family":"Robert","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Fraunhofer Center for Machine Learning,Karlsruhe,Germany"}]},{"given":"Jurgen","family":"Beyerer","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Fraunhofer Center for Machine Learning,Karlsruhe,Germany"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-08795-5_18"},{"key":"ref11","article-title":"Predicting process behaviour using deep learning","volume":"abs 1612 4600","author":"evermann","year":"2016","journal-title":"CoRR"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59536-8_30"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CBI.2017.46"},{"journal-title":"Bpi challenge 2013","year":"2013","author":"steeman","key":"ref14"},{"journal-title":"Bpi challenge 2012","year":"2012","author":"van dongen","key":"ref15"},{"journal-title":"TensorFlow Large-Scale Machine Learning on Heterogeneous Systems","year":"2015","author":"abadi","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"journal-title":"Layer normalization","year":"2016","author":"ba","key":"ref18"},{"key":"ref19","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"The Journal of Machine Learning Research"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.25300\/MISQ\/2016\/40.4.10"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4471-4739-8_13"},{"key":"ref6","first-page":"1","article-title":"Ieee standard for extensible event stream (xes) for achieving interoperability in event logs and event streams","author":"group","year":"2016","journal-title":"IEEE Std 1849–2016"},{"key":"ref5","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ISCMI47871.2019.9004296"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-49851-4_1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88871-0_22"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2010.09.001"},{"journal-title":"Neural machine translation by jointly learning to align and translate","year":"2014","author":"bahdanau","key":"ref9"},{"journal-title":"Rethinking the inception architecture for computer vision","year":"2015","author":"szegedy","key":"ref20"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1285"},{"journal-title":"Adam A method for stochastic optimization","year":"2014","author":"kingma","key":"ref21"},{"journal-title":"Generating long sequences with sparse transformers","year":"2019","author":"child","key":"ref23"}],"event":{"name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","start":{"date-parts":[[2020,2,19]]},"location":"Fukuoka, Japan","end":{"date-parts":[[2020,2,21]]}},"container-title":["2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9046688\/9064864\/09065057.pdf?arnumber=9065057","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:15:49Z","timestamp":1656375349000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9065057\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/icaiic48513.2020.9065057","relation":{},"subject":[],"published":{"date-parts":[[2020,2]]}}} proceedings-article https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html crossref PersonAuthorFirstName_1,PersonAuthorLastName_1,PersonAuthorFirstName_2,PersonAuthorLastName_2,PersonAuthorFirstName_3,PersonAuthorLastName_3,PersonAuthorFirstName_4,PersonAuthorLastName_4,Enrichmentconference_title,Enrichmentconference_place,PublisherName,TitleMain_1,TitleParent_1,PageNumber,PageFirst,PageLast,CompletedYear,Enrichmentlocal_crossrefLicence 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Fukuoka, Japan doi-import false true Patrick Philipp Ruben Jacob Sebastian Robert Jurgen Beyerer