VTMine for Visio: A Graphical Tool for Modeling in Process Mining

被引:1
|
作者
Shershakov, S. A. [1 ]
机构
[1] HSE Univ, Moscow 101000, Russia
关键词
process modeling; process mining; experiment models; graphical tool; experiments automation;
D O I
10.3103/S0146411621070282
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Process-aware information systems (PAISs) is a special class of information systems intended to support the tasks of initialization, end-to-end management, and completion of business processes. During their operation such systems accumulate a large amount of data that are stored in the form of event logs. Event logs are a valuable source of knowledge about the actual behavior of a system. For example, they include (i) information about the discrepancy between the real and prescribed behavior of the system, (ii) information for identifying the bottlenecks and performance issues, and (iii) information for detecting the antipatterns of building a business system. These problems are studied in the discipline called process mining. The practical application of the process mining methods and practices is carried out using specialized software for data analysts. The subject area of the process analysis involves the work of an analyst with a large number of graphical models. Such work can be more efficiently with a convenient graphical modeling tool. This paper discusses the principles of designing a graphical tool VTMine for Visio for process modeling, based on the widespread application Microsoft Visio for business intelligence. The features of the architecture design of the software extension for application in the process mining area are presented along with the features of integration with existing libraries and tools for working with data. The usage of the developed tool for solving various types of tasks in modeling and analysis of processes is demonstrated on a set of experimental schemes.
引用
收藏
页码:847 / 865
页数:19
相关论文
共 50 条
  • [41] PROMOTE: A Process Mining Tool for Embedded System Development
    Leppakoski, Arttu
    Hamalainen, Timo D.
    PRODUCT-FOCUSED SOFTWARE PROCESS IMPROVEMENT (PROFES 2016), 2016, 10027 : 529 - 538
  • [42] Process Mining for Six SigmaA Guideline and Tool Support
    Teun Graafmans
    Oktay Turetken
    Hans Poppelaars
    Dirk Fahland
    Business & Information Systems Engineering, 2021, 63 : 277 - 300
  • [43] PrOnto: an Ontology Driven Business Process Mining Tool
    Bistarelli, Stefano
    Di Noia, Tommaso
    Mongiello, Marina
    Nocera, Francesco
    KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS, 2017, 112 : 306 - 315
  • [44] A tool for compiling Declarative Process Mining problems in ASP
    Chiariello, Francesco
    Maggi, Fabrizio Maria
    Patrizi, Fabio
    SOFTWARE IMPACTS, 2022, 14
  • [45] Process Mining for Six Sigma A Guideline and Tool Support
    Graafmans, Teun
    Turetken, Oktay
    Poppelaars, Hans
    Fahland, Dirk
    BUSINESS & INFORMATION SYSTEMS ENGINEERING, 2021, 63 (03) : 277 - 300
  • [46] MODELING METHODS OF TECHNOLOGICAL PROCESS IN SLAUGHTER MINING
    Teodora, Furdui Ersilia
    Eduard, Edelhauser
    Lucian, Lupu-Dima
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON MANUFACTURING SCIENCE AND EDUCATION (MSE 2011), VOL I, 2011, : 421 - 424
  • [47] A process mining methodology for modeling unstructured processes
    Stefanini, Alessandro
    Aloini, Davide
    Benevento, Elisabetta
    Dulmin, Riccardo
    Mininno, Valeria
    KNOWLEDGE AND PROCESS MANAGEMENT, 2020, 27 (04) : 294 - 310
  • [48] ANALYSIS AND MODELING OF A PROPOSED MINING AND BENEFICIATION PROCESS
    HODGSON, TJ
    KING, RE
    MCCLAVE, JT
    SULLIVAN, JH
    ZEGEL, WC
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 1987, 26 (11) : 2223 - 2228
  • [49] Modeling the business process by mining multiple databases
    Sanjeev, AP
    Zytkow, JM
    PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY, 1998, 1510 : 432 - 440
  • [50] Data mining with graphical models
    Kruse, R
    Borgelt, C
    DISCOVERY SCIENCE, PROCEEDINGS, 2002, 2534 : 2 - 11