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Continuous update of business process trees using Continuous Inductive Miner

Pawlak Tomasz P., Górka Bartosz

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2023

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Vol. 71, nr 1

art. no. e143551

EN

Business processes are omnipresent in nowadays economy: companies operate repetitively to achieve their goals, e.g., deliver goods, complete orders. The business process model is the key to understanding, managing, controlling, and verifying the operations of a company. Modeling of business processes may be a legal requirement in some market segments, e.g., financial in the European Union, and a prerequisite for certification, e.g., of the ISO-9001 standard. However, business processes naturally evolve, and continuous model adaptation is essential for rapid spot and reaction to changes in the process. The main contribution of this work is the Continuous Inductive Miner (CIM) algorithm that discovers and continuously adapts the process tree, an established representation of the process model, using the batches of event logs of the business process. CIM joins the exclusive guarantees of its two batch predecessors, the Inductive Miner (IM) and the Inductive Miner – directlyfollows-based (IMd): perfectly fit and sound models, and single-pass event log processing, respectively. CIM offers much shorter computation times in the update scenario than IM and IMd. CIM employs statistical information to work around the need to remember event logs as IM does while ensuring the perfect fit, contrary to IMd.

2

Guidelines for recording transport event logs

Dramski M.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

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2018

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nr 53 (125)

102--105

EN

A process is an ordered set of related activities taking place in a given time. Processes are present in all branches of the economy, engineering, science, etc. Due to the huge amount of data produced the rapid development of data mining techniques has been observed. Similar methods are also used in the context of processes and are called process mining. The main task of process mining is to create a process model, which is used to reason about the process and to make decisions inside it. The process model may be used to discuss responsibilities, simulations, predictions, etc. The main data structures in process mining are event logs. It is always very important to have correct data which makes creating a reliable process model possible. In this paper the basic guidelines for recording such event logs have been described and conclusions were drawn. The main focus of this research was transport problems.

3

Models of temporal dependencies for a probabilistic knowledge base

Chala O.

ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes

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2018

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Vol. 7, No 3

53--58

EN

The article presents models of temporal dependences for constructing probabilistic temporal rules in the Markov Logical Networks. Such rules describe the relations between the states of a control object and taking account the possibility of integrating different approaches of management according to the paradigm of «Enterprise 2.0» knowledge sharing. The proposed models define constraints and conditions for changing the states of a control object, which allows predicting possible variants of its behavior in relation to the current state and providing decision support based on a choice of the most likely variants.

4

The alpha algorithm in modeling of the ship’s route

Dramski M.

Archives of Transport System Telematics

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2016

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Vol. 9, iss. 2

8--11

EN

In this paper the use of alpha algorithm in modeling of the ship’s route is described. Based on event log obtained from real data, a Petri net was created. This model let us to review the whole process of the ship’s route and take some interesting observations.