5 research outputs found
ΠΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΡΠ·ΡΠΊ DPMine Π΄Π»Ρ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΠΈ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠΎΠ² Π² ΠΎΠ±Π»Π°ΡΡΠΈ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΠΈ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ²
Process mining is a new direction in the field of modeling and analysis of processes, where the use of information from event logs describing the history of the system behavior plays an important role. Methods and approaches used in the process mining are often based on various heuristics, and experiments with large event logs are crucial for the study and comparison of the developed methods and algorithms. Such experiments are very time consuming, so automation of experiments is an important task in the field of process mining. This paper presents the language DPMine developed specifically to describe and carry out experiments on the discovery and analysis of process models. The basic concepts of the DPMine language as well as principles and mechanisms of its extension are described. Ways of integration of the DPMine language as dynamically loaded components into the VTMine modeling tool are considered. An illustrating example of an experiment for building a fuzzy model of the process discovered from the log data stored in a normalized database is given.ΠΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΠ΅ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² (process mining) β ΡΡΠΎ Π½ΠΎΠ²ΠΎΠ΅ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ², Π² ΠΊΠΎΡΠΎΡΠΎΠΌ Π²Π°ΠΆΠ½ΡΡ ΡΠΎΠ»Ρ ΠΈΠ³ΡΠ°Π΅Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· ΠΆΡΡΠ½Π°Π»ΠΎΠ² (Π»ΠΎΠ³ΠΎΠ²) ΡΠΎΠ±ΡΡΠΈΠΉ, Ρ
ΡΠ°Π½ΡΡΠΈΡ
ΠΈΡΡΠΎΡΠΈΡ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ. ΠΠ΅ΡΠΎΠ΄Ρ ΠΈ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΠΌΡΠ΅ ΠΏΡΠΈ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ², ΡΠ°ΡΡΠΎ ΠΎΠΏΠΈΡΠ°ΡΡΡΡ Π½Π° ΡΠ°Π·Π»ΠΈΡΠ½ΡΠ΅ ΡΠ²ΡΠΈΡΡΠΈΠΊΠΈ, ΠΈ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡ Ρ Π±ΠΎΠ»ΡΡΠΈΠΌΠΈ Π»ΠΎΠ³Π°ΠΌΠΈ ΡΠΎΠ±ΡΡΠΈΠΉ Π²Π°ΠΆΠ½Ρ Π΄Π»Ρ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΠΌΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΈ Π°Π»Π³ΠΎΡΠΈΡΠΌΠΎΠ². Π’Π°ΠΊΠΈΠ΅ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡ Π²Π΅ΡΡΠΌΠ° ΡΡΡΠ΄ΠΎΠ΅ΠΌΠΊΠΈ, ΠΏΠΎΡΡΠΎΠΌΡ ΠΈΡ
Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π·Π°Π΄Π°ΡΠ΅ΠΉ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ². Π Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ ΡΠ·ΡΠΊ DPMine, ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΡΠΉ ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎ Π΄Π»Ρ ΠΎΠΏΠΈΡΠ°Π½ΠΈΡ ΠΈ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠΎΠ² ΠΏΠΎ ΠΈΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΈ Π°Π½Π°Π»ΠΈΠ·Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ². ΠΠ°Π΅ΡΡΡ ΠΎΠΏΠΈΡΠ°Π½ΠΈΠ΅ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΠΉ ΡΠ·ΡΠΊΠ°, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΎΠ² ΠΈ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠΎΠ² Π΅Π³ΠΎ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΡ. Π Π°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΡΡ Π²ΠΎΠΏΡΠΎΡΡ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ ΡΠ·ΡΠΊΠ° Π² ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½Ρ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ VTMine Π² Π²ΠΈΠ΄Π΅ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΈ Π·Π°Π³ΡΡΠΆΠ°Π΅ΠΌΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ². ΠΡΠΈΠ²ΠΎΠ΄ΠΈΡΡΡ ΠΏΡΠΈΠΌΠ΅Ρ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ° ΠΏΠΎ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΏΠΎ Π»ΠΎΠ³Ρ Π΄Π°Π½Π½ΡΡ
, Ρ
ΡΠ°Π½ΡΡΠ΅ΠΌΡΡΡ Π² Π²ΠΈΠ΄Π΅ Π½ΠΎΡΠΌΠ°Π»ΠΈΠ·ΠΎΠ²Π°Π½Π½ΠΎΠΉ Π±Π°Π·Ρ Π΄Π°Π½Π½ΡΡ
βVTMine for Visioβ: ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½Ρ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π² ΠΎΠ±Π»Π°ΡΡΠΈ Process Mining
Process-Aware Information Systems (PAIS) is a special class of the IS intended for the support the tasks of initialization, end-to-end management and completion of business processes. During the operation such systems accumulate a large number of data that are recorded in the form of the event logs. Event logs are a valuable source of knowledge about the actual behavior of a system. For example, there can be found information about the discrepancy between the real and the prescribed behavior of the system; to identify bottlenecks and performance issues; to detect anti-patterns of building a business system. These problems are studied by the discipline called βProcess Miningβ.The practical application of the process mining methods and practices is carried out using the 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 will be more efficient with a convenient graphical modeling tool. The paper discusses the principles of building a graphical tool βVTMine for Visioβ for the process modeling, based on the widespread application for business intelligence Microsoft Visio. There are presented features of the architecture design of the software extension for application in the process mining domain and integration with the existing libraries and tools for working with data. The application of the developed tool for solving various types of tasks for modeling and analysis of processes is demonstrated on a set of experimental schemes.ΠΡΠΎΡΠ΅ΡΡΠ½ΠΎ-ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ (ΠΠΠΠ‘) β ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΡΠΉ ΠΊΠ»Π°ΡΡ ΠΠ‘ Π΄Π»Ρ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ Π·Π°Π΄Π°Ρ ΠΏΠΎ ΠΈΠ½ΠΈΡΠΈΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ, ΡΠΊΠ²ΠΎΠ·Π½ΠΎΠΌΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΈ Π·Π°Π²Π΅ΡΡΠ΅Π½ΠΈΡ Π±ΠΈΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ². Π ΠΏΡΠΎΡΠ΅ΡΡΠ΅ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΠΊΠΈΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ Π½Π°ΠΊΠ°ΠΏΠ»ΠΈΠ²Π°ΡΡ Π±ΠΎΠ»ΡΡΠΎΠ΅ ΡΠΈΡΠ»ΠΎ Π΄Π°Π½Π½ΡΡ
, ΠΊΠΎΡΠΎΡΡΠ΅ Π·Π°ΠΏΠΈΡΡΠ²Π°ΡΡΡΡ Π² Π²ΠΈΠ΄Π΅ ΠΆΡΡΠ½Π°Π»ΠΎΠ² ΡΠΎΠ±ΡΡΠΈΠΉ. ΠΡΡΠ½Π°Π»Ρ ΡΠΎΠ±ΡΡΠΈΠΉ ΡΠ²Π»ΡΡΡΡΡ ΡΠ΅Π½Π½ΡΠΌ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΎΠΌ Π·Π½Π°Π½ΠΈΠΉ ΠΎ ΡΠ΅Π°Π»ΡΠ½ΠΎΠΌ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠΈ ΡΠΈΡΡΠ΅ΠΌΡ. ΠΠ°ΠΏΡΠΈΠΌΠ΅Ρ, Π² Π½ΠΈΡ
ΠΌΠΎΠΆΠ½ΠΎ ΠΎΠ±Π½Π°ΡΡΠΆΠΈΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΎ Π½Π΅ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ ΡΠ΅Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈ ΠΆΠ΅Π»Π°Π΅ΠΌΠΎΠ³ΠΎ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ; ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ ΡΠ·ΠΊΠΈΠ΅ ΠΌΠ΅ΡΡΠ° ΠΈ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ Ρ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡΡ; Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠΎΠ²Π°ΡΡ Π°Π½ΡΠΈ-ΠΏΠ°ΡΡΠ΅ΡΠ½Ρ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ Π±ΠΈΠ·Π½Π΅Ρ-ΡΠΈΡΡΠ΅ΠΌΡ. ΠΠ·ΡΡΠ΅Π½ΠΈΠ΅ΠΌ ΡΡΠΈΡ
Π·Π°Π΄Π°Ρ Π·Π°Π½ΠΈΠΌΠ°Π΅ΡΡΡ Π΄ΠΈΡΡΠΈΠΏΠ»ΠΈΠ½Π° Β«ΠΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΠ΅ ΠΈ Π°Π½Π°Π»ΠΈΠ· ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ²Β» (Process Mining).ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΈ ΠΏΡΠ°ΠΊΡΠΈΠΊ Process Mining ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ΅ΡΡΡ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ (ΠΠ) Π΄Π»Ρ Π°Π½Π°Π»ΠΈΡΠΈΠΊΠΎΠ² Π΄Π°Π½Π½ΡΡ
. ΠΡΠ΅Π΄ΠΌΠ΅ΡΠ½Π°Ρ ΠΎΠ±Π»Π°ΡΡΡ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΠΏΠΎΠ΄ΡΠ°Π·ΡΠΌΠ΅Π²Π°Π΅Ρ ΡΠ°Π±ΠΎΡΡ Π°Π½Π°Π»ΠΈΡΠΈΠΊΠ° Ρ Π±ΠΎΠ»ΡΡΠΈΠΌ ΡΠΈΡΠ»ΠΎΠΌ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ. Π’Π°ΠΊΠ°Ρ ΡΠ°Π±ΠΎΡΠ° Π±ΡΠ΄Π΅Ρ Π±ΠΎΠ»Π΅Π΅ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΠΏΡΠΈ Π½Π°Π»ΠΈΡΠΈΠΈ ΡΠ΄ΠΎΠ±Π½ΠΎΠ³ΠΎ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ° Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ. Π Π½Π°ΡΡΠΎΡΡΠ΅ΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΡΡ ΠΏΡΠΈΠ½ΡΠΈΠΏΡ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ° Β«VTMine for VisioΒ» ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π½Π° Π±Π°Π·Π΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡ Π΄Π»Ρ Π±ΠΈΠ·Π½Π΅Ρ-Π°Π½Π°Π»ΠΈΡΠΈΠΊΠΈ Microsoft Visio. ΠΡΠΈΠ²ΠΎΠ΄ΡΡΡΡ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΡ Π΄Π»Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π² ΠΎΠ±Π»Π°ΡΡΠΈ Process Mining ΠΈ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ Ρ ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΠΌΠΈ Π±ΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊΠ°ΠΌΠΈ ΠΈ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌΠΈ Π΄Π»Ρ ΡΠ°Π±ΠΎΡΡ Ρ Π΄Π°Π½Π½ΡΠΌΠΈ. ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡ Π΄Π»Ρ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΠΎΠ³ΠΎ Π²ΠΈΠ΄Π° Π·Π°Π΄Π°Ρ ΠΏΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ Π°Π½Π°Π»ΠΈΠ·Ρ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΠ΅ΡΡΡ Π½Π° Π½Π°Π±ΠΎΡΠ΅ ΡΡ
Π΅ΠΌ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠΎΠ²
ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΆΡΡΠ½Π°Π»ΠΎΠ² ΡΠΎΠ±ΡΡΠΈΠΉ Π΄Π»Ρ Π»ΠΎΠΊΠ°Π»ΡΠ½ΠΎΠΉ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²ΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ²
During the life-cycle of an Information System (IS) its actual behaviour may not correspond to the original system model. However, to the IS support it is very important to have the latest model that reflects the current system behaviour. To correct the model, the information from the event log of the system may be used. In this paper, we consider the problem of process model adjustment (correction) using the information from an event log. The input data for this task are the initial process model (a Petri net) and the event log. The result of correction should be a new process model, better reflecting the real IS behavior than the initial model. The new model could be also built from scratch, for example, with the help of one of the known algorithms for automatic synthesis of the process model from an event log. However, this may lead to crucial changes in the structure of the original model, and it will be difficult to compare the new model with the initial one, hindering its understanding andΒ analysis. It is important to keep the initial structure of the model as much as possible. In this paper, we propose a method for process model correction based on the principle of βdivide and conquerβ. The initial model is decomposed in several fragments. For each fragment its conformance to the event log is checked. Fragments which do not match the log are replaced by newly synthesized ones. The new model is then assembled from the fragments via transition fusion. The experiments demonstrate that our correction algorithm gives good results when it is used for correcting local discrepancies. The paper presents the description of the algorithm, the formal justification for its correctness, as well as the results of experimental testing by some artificial examples.Π Ρ
ΠΎΠ΄Π΅ ΠΆΠΈΠ·Π½Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠΈΠΊΠ»Π° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ (ΠΠ‘) Π΅Π΅ ΡΠ΅Π°Π»ΡΠ½ΠΎΠ΅ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΌΠΎΠΆΠ΅Ρ ΠΏΠ΅ΡΠ΅ΡΡΠ°ΡΡ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΎΠ²Π°ΡΡ ΠΈΡΡ
ΠΎΠ΄Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠΈΡΡΠ΅ΠΌΡ. ΠΠ΅ΠΆΠ΄Ρ ΡΠ΅ΠΌ Π΄Π»Ρ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ ΡΠΈΡΡΠ΅ΠΌΡ ΠΎΡΠ΅Π½Ρ Π²Π°ΠΆΠ½ΠΎ ΠΈΠΌΠ΅ΡΡ Π°ΠΊΡΡΠ°Π»ΡΠ½ΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ, ΠΎΡΡΠ°ΠΆΠ°ΡΡΡΡ ΡΠ΅ΠΊΡΡΠ΅Π΅ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ. ΠΠ»Ρ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²ΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΌΠΎΠΆΠ½ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΈΠ· ΠΆΡΡΠ½Π°Π»Π° ΡΠΎΠ±ΡΡΠΈΠΉ ΡΠΈΡΡΠ΅ΠΌΡ. ΠΡΡΠ½Π°Π»Ρ ΡΠΎΠ±ΡΡΠΈΠΉ ΠΏΡΠΎΡΠ΅ΡΡΠ½ΠΎ-ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ ΡΠΎΠ΄Π΅ΡΠΆΠ°Ρ Π·Π°ΠΏΠΈΡΡ ΠΈΡΡΠΎΡΠΈΠΈ ΠΈΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΈΠ²Π°Π΅ΠΌΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π² Π²ΠΈΠ΄Π΅ Π±ΠΎΠ»Π΅Π΅ ΠΈΠ»ΠΈ ΠΌΠ΅Π½Π΅Π΅ Π΄Π΅ΡΠ°Π»ΡΠ½ΡΡ
ΡΠΏΠΈΡΠΊΠΎΠ² ΡΠΎΠ±ΡΡΠΈΠΉ. Π’Π°ΠΊΠΈΠ΅ ΠΆΡΡΠ½Π°Π»Ρ, ΠΊΠ°ΠΊ ΠΏΡΠ°Π²ΠΈΠ»ΠΎ, Π·Π°ΠΏΠΈΡΡΠ²Π°ΡΡΡΡ Π²ΡΠ΅ΠΌΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌ ΠΠ‘. ΠΡΠ° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΌΠΎΠΆΠ΅Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡΡΡ Π΄Π»Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠ΅Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΠ‘ ΠΈ Π΅Π΅ ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ. Π ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π·Π°Π΄Π°ΡΠ° ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²ΠΊΠΈ (ΠΈΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ) ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· ΠΆΡΡΠ½Π°Π»Π° ΡΠΎΠ±ΡΡΠΈΠΉ. ΠΡΡ
ΠΎΠ΄Π½ΡΠΌΠΈ Π΄Π°Π½Π½ΡΠΌΠΈ Π΄Π»Ρ ΡΡΠΎΠΉ Π·Π°Π΄Π°ΡΠΈ ΡΠ²Π»ΡΡΡΡΡ ΠΏΠ΅ΡΠ²ΠΎΠ½Π°ΡΠ°Π»ΡΠ½Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ° Π² Π²ΠΈΠ΄Π΅ ΡΠ΅ΡΠΈ ΠΠ΅ΡΡΠΈ ΠΈ ΠΆΡΡΠ½Π°Π» ΡΠΎΠ±ΡΡΠΈΠΉ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠΌ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²ΠΊΠΈ Π΄ΠΎΠ»ΠΆΠ½Π° Π±ΡΡΡ Π½ΠΎΠ²Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ°, Π»ΡΡΡΠ΅ ΠΎΡΠΎΠ±ΡΠ°ΠΆΠ°ΡΡΠ°Ρ ΡΠ΅Π°Π»ΡΠ½ΠΎΠ΅ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΠ‘, ΡΠ΅ΠΌ ΠΈΡΡ
ΠΎΠ΄Π½Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ. ΠΠΊΡΡΠ°Π»ΡΠ½Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΏΠΎΡΡΡΠΎΠ΅Π½Π° ΠΈ ΠΏΠΎΠ»Π½ΠΎΡΡΡΡ Π·Π°Π½ΠΎΠ²ΠΎ, Π½Π°ΠΏΡΠΈΠΌΠ΅Ρ, Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΈΠ· ΠΈΠ·Π²Π΅ΡΡΠ½ΡΡ
Π°Π»Π³ΠΎΡΠΈΡΠΌΠΎΠ² Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΈΠ½ΡΠ΅Π·Π° ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΏΠΎ ΠΆΡΡΠ½Π°Π»Ρ ΡΠΎΠ±ΡΡΠΈΠΉ. ΠΠ΄Π½Π°ΠΊΠΎ ΡΡΡΡΠΊΡΡΡΠ° ΠΈΡΡ
ΠΎΠ΄Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡΠΈ ΡΡΠΎΠΌ ΠΌΠΎΠΆΠ΅Ρ ΠΏΠΎΠ»Π½ΠΎΡΡΡΡ ΠΈΠ·ΠΌΠ΅Π½ΠΈΡΡΡΡ. ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ Π±ΡΠ΄Π΅Ρ ΡΡΡΠ΄Π½ΠΎ ΡΠΎΠΏΠΎΡΡΠ°Π²ΠΈΡΡ Ρ ΠΏΡΠ΅ΠΆΠ½Π΅ΠΉ ΠΌΠΎΠ΄Π΅Π»ΡΡ ΠΏΡΠΎΡΠ΅ΡΡΠ°, ΡΡΠΎ Π·Π°ΡΡΡΠ΄Π½ΠΈΡ Π΅Π΅ ΠΏΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΠΈ Π°Π½Π°Π»ΠΈΠ·. ΠΠΎΡΡΠΎΠΌΡ ΠΏΡΠΈ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²ΠΊΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π²Π°ΠΆΠ½ΠΎ ΠΏΠΎ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΡΠΎΡ
ΡΠ°Π½ΠΈΡΡ Π΅Π΅ ΠΏΡΠ΅ΠΆΠ½ΡΡ ΡΡΡΡΠΊΡΡΡΡ. ΠΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΡΠΉ Π² Π½Π°ΡΡΠΎΡΡΠ΅ΠΉ ΡΠ°Π±ΠΎΡΠ΅ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²ΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΎΡΠ½ΠΎΠ²Π°Π½ Π½Π° ΠΏΡΠΈΠ½ΡΠΈΠΏΠ΅ Β«ΡΠ°Π·Π΄Π΅Π»ΡΠΉ ΠΈ Π²Π»Π°ΡΡΠ²ΡΠΉΒ». ΠΡΡ
ΠΎΠ΄Π½Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ° Π΄Π΅ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡΡΠ΅ΡΡΡ Π½Π° ΡΡΠ°Π³ΠΌΠ΅Π½ΡΡ. ΠΠ»Ρ ΠΊΠ°ΠΆΠ΄ΠΎΠ³ΠΎ ΠΈΠ· ΡΡΠ°Π³ΠΌΠ΅Π½ΡΠΎΠ² ΠΏΡΠΎΠ²Π΅ΡΡΠ΅ΡΡΡ, ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΠ΅Ρ Π»ΠΈ ΠΎΠ½ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠΌΡ ΠΆΡΡΠ½Π°Π»Ρ ΡΠΎΠ±ΡΡΠΈΠΉ. Π€ΡΠ°Π³ΠΌΠ΅Π½ΡΡ, Π΄Π»Ρ ΠΊΠΎΡΠΎΡΡΡ
Π²ΡΡΠ²Π»Π΅Π½Ρ Π½Π΅ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΡ, Π·Π°ΠΌΠ΅Π½ΡΡΡΡΡ Π½Π° Π·Π°Π½ΠΎΠ²ΠΎ ΡΠΈΠ½ΡΠ΅Π·ΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅. ΠΠΎΠ²Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠΎΠ±ΠΈΡΠ°Π΅ΡΡΡ ΠΈΠ· ΡΡΠ°Π³ΠΌΠ΅Π½ΡΠΎΠ² ΠΏΡΡΠ΅ΠΌ ΡΠ»ΠΈΡΠ½ΠΈΡ ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄ΠΎΠ². ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠ΅ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ, ΡΡΠΎ Π½Π°Ρ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²ΠΊΠΈ Π΄Π°Π΅Ρ Ρ
ΠΎΡΠΎΡΠΈΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ, Π΅ΡΠ»ΠΈ ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΡΡΡ Π΄Π»Ρ ΠΈΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ Π»ΠΎΠΊΠ°Π»ΡΠ½ΡΡ
Π½Π΅ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΉ. Π Π°Π±ΠΎΡΠ° ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΠΎΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°, ΡΠΎΡΠΌΠ°Π»ΡΠ½ΠΎΠ΅ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠ΅ Π΅Π³ΠΎ ΠΊΠΎΡΡΠ΅ΠΊΡΠ½ΠΎΡΡΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π½Π° ΠΈΡΠΊΡΡΡΡΠ²Π΅Π½Π½ΡΡ
ΠΏΡΠΈΠΌΠ΅ΡΠ°Ρ
.
DPMine Graphical Language for Automation of Experiments in Process Mining
Process mining is a new direction in the field of modeling and analysis of processes, where the use of information from event logs describing the history of the system behavior plays an important role. Methods and approaches used in the process mining are often based on various heuristics, and experiments with large event logs are crucial for the study and comparison of the developed methods and algorithms. Such experiments are very time consuming, so automation of experiments is an important task in the field of process mining. This paper presents the language DPMine developed specifically to describe and carry out experiments on the discovery and analysis of process models. The basic concepts of the DPMine language as well as principles and mechanisms of its extension are described. Ways of integration of the DPMine language as dynamically loaded components into the VTMine modeling tool are considered. An illustrating example of an experiment for building a fuzzy model of the process discovered from the log data stored in a normalized database is given