Enabling Multi-process Discovery on Graph Databases

被引:5
|
作者
Eldin, Ali Nour [1 ,2 ]
Assy, Nour [1 ]
Kobeissi, Meriana [1 ,3 ]
Baudot, Jonathan [2 ]
Gaaloul, Walid [1 ]
机构
[1] Inst Polytech Paris, Telecom SudParis, Paris, France
[2] Bonitasoft, Grenoble, France
[3] Lebanese Univ, Fac Sci, Beirut, Lebanon
来源
COOPERATIVE INFORMATION SYSTEMS (COOPIS 2022) | 2022年 / 13591卷
关键词
Object-centric; Process mining; Process discovery; Property graph; Cypher language;
D O I
10.1007/978-3-031-17834-4_7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the abundance of event data, the challenge of enabling process discovery in the large has attracted the community attention. Several works addressed the problem by performing process discovery directly on relational databases, instead of the traditional file based computations. Preliminary results show that moving (parts of) process discovery to the database engine outperforms file based computations. However, all existing works consider the traditional storage of event data which assumes that a clear and predefined process instance notion exists, and that events are correlated to one process instance. In this work, we go two steps further. First, we address the problem of process discovery on object-centric event data which allows several process instance notions to be flexibly defined. We refer to it as multi-process discovery Second, motivated by the intrinsic nature of process discovery that searches for relationships in event data, we address the question of how graph-based storage of object-centric event data improves the performance of multi-process discovery? We propose in-database process discovery operators based on labeled property graphs. We use Neo4j as a DBMS and Cypher as a query language. We compare different discovery strategies that involve graph and relational databases. Our results show that process discovery in graph databases outperform existing approaches.
引用
收藏
页码:112 / 130
页数:19
相关论文
共 50 条
  • [1] Storing and Querying Multi-dimensional Process Event Logs Using Graph Databases
    Esser, Stefan
    Fahland, Dirk
    BUSINESS PROCESS MANAGEMENT WORKSHOPS (BPM 2019), 2019, 362 : 632 - 644
  • [2] Multi-Dimensional Event Data in Graph Databases
    Esser, Stefan
    Fahland, Dirk
    JOURNAL ON DATA SEMANTICS, 2021, 10 (1-2) : 109 - 141
  • [3] Discovery of Multi-perspective Declarative Process Models
    Schoenig, Stefan
    Di Ciccio, Claudio
    Maggi, Fabrizio M.
    Mendling, Jan
    SERVICE-ORIENTED COMPUTING, (ICSOC 2016), 2016, 9936 : 87 - 103
  • [4] Mapping RDF Databases to Property Graph Databases
    Angles, Renzo
    Thakkar, Harsh
    Tomaszuk, Dominik
    IEEE ACCESS, 2020, 8 : 86091 - 86110
  • [5] On Process Discovery Experimentation: Addressing the Need for Research Methodology in Process Discovery
    Rehse, Jana-rebecca
    Leemans, Sander J. J.
    Fettke, Peter
    van der Werf, Jan martijn e. m.
    ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 2024, 34 (01)
  • [6] Interactive Multi-interest Process Pattern Discovery
    Vazifehdoostirani, Mozhgan
    Genga, Laura
    Lu, Xixi
    Verhoeven, Rob
    van Laarhoven, Hanneke
    Dijkman, Remco
    BUSINESS PROCESS MANAGEMENT, BPM 2023, 2023, 14159 : 303 - 319
  • [7] Process Mining: On the Fly Process Discovery
    Boushaba, Souhail
    Issam Kabbaj, Mohammed
    Bakkoury, Zohra
    Mohamed Matais, Said
    PROCEEDINGS OF THE MEDITERRANEAN CONFERENCE ON INFORMATION & COMMUNICATION TECHNOLOGIES 2015 (MEDCT 2015), VOL 2, 2016, 381 : 79 - 89
  • [8] Enabling the Discovery of Manual Processes Using a Multi-modal Activity Recognition Approach
    Rebmann, Adrian
    Emrich, Andreas
    Fettke, Peter
    BUSINESS PROCESS MANAGEMENT WORKSHOPS (BPM 2019), 2019, 362 : 130 - 141
  • [9] Process Discovery Automated Approach for Block Discovery
    Boushaba, Souhail
    Issam Kabbaj, Mohammed
    Bakkoury, Zohra
    PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING (ENASE 2014), 2014, : 204 - 211
  • [10] Technical Survey Graph Databases and Applications
    Wang, Shao-Ting
    Jin, Jennifer
    Rivett, Pete
    Kitazawa, Atsushi
    INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING, 2015, 9 (04) : 523 - 545