A native operator for process discovery
| Autor: | Syamsiyah, Alifah, van Dongen, Boudewijn F., Dijkman, Remco M., Pernul, Günther, Hartmann, Sven, Ma, Hui, Hameurlain, Abdelkader, Wagner, Roland R. |
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| Přispěvatelé: | Information Systems IE&IS, Process Science |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Relational database
Process (engineering) Event (computing) Computer science Process discovery Process mining 02 engineering and technology computer.software_genre Business process discovery Operator (computer programming) SQL operator 020204 information systems 0202 electrical engineering electronic engineering information engineering Information system 020201 artificial intelligence & image processing Data mining computer |
| Zdroj: | Database and Expert Systems Applications-29th International Conference, DEXA 2018, Proceedings, 292-300 STARTPAGE=292;ENDPAGE=300;TITLE=Database and Expert Systems Applications-29th International Conference, DEXA 2018, Proceedings Lecture Notes in Computer Science ISBN: 9783319988115 DEXA (2) |
| Popis: | The goal of process mining is to gain insights into operational processes through the analysis of events recorded by information systems. Typically, this is done in three phases. Firstly, events are extracted from a data store into an event log. Secondly, an intermediate structure is built in memory and finally, this intermediate structure is converted into a process model or other analysis results. In this paper, we propose a native SQL operator for direct process discovery on relational databases. We merge steps 1 and 2 by defining a native operator for the simplest form of the intermediate structure, called the “directly follows relation”. We evaluate our work on big event data and the experimental results show that it performs faster than the state-of-the-art of database approaches. |
| Databáze: | OpenAIRE |
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