Procesno rudarjenje s programom ProM

GRAH, DOMINIK (author), Bajec, Marko (mentor)

Osnovni namen diplomskega dela je prikazati uporabo procesnega rudarjenja na realnem primeru. Prav tako pa raziskati in podati prednosti ter slabosti procesnega rudarjenja. V teoretičnem delu so podrobneje predstavljeni: namen uporabe procesnega rudarjenje, njegove možnosti za uporabo, različni algoritmi, prav tako pa nekaj možnih procesnih modelov za predstavitev procesa. V zadnjem delu teoretičnega dela pa je predstavljeno orodje ProM in ostala možna orodja, prav tako pa primerjava med njimi. V praktičnem delu pa je predstavljena uporaba prikazanih tehnik na realnem primeru iz okolja. Kot rezultat analize s programom ProM dobimo različne modele, mreže in grafe, s pomočjo katerih lahko potem analiziramo proces.

• Language: Slovenian
• Keywords: Procesno rudarjenje, procesni model, petrijeve mreže, c-mreže, dnevnik dogodkov, alfa algoritem, hevristično rudarjenje, inductive miner, fuzzy miner, token replay, organizacijski vidik, časovni vidik.
• Work type: Undergraduate thesis
• Organization: FRI - Faculty of Computer and Information Science
• Year: 2015
• PID: 20.500.12556/RUL-72046
• Publication date in RUL: 19.08.2015

Secondary language

• Language: English
• Title: Process mining with ProM

Abstract

The primary purpose of this diploma is to demonstrate the use of process mining on a real life case and also to explore advantages and disadvantages of process mining. The theoretical part presents in detail the purposes and reasons of applying process mining to organizations, different algorithms for process mining, and some possible process models for representation of processes. The last chapter in theoretical part presents the ProM tool, which is used for process mining, and also other popular tools. The last part is practical part, which shows the usage of process mining techniques on a real life example. As a result of analysis with program ProM, we get different models, networks and graphs, which we can then use to analyze the process.

• Keywords: Process mining, process model, Petri nets, c-nets, event logs, alpha algorithm, heuristic mining, inductive miner, fuzzy miner, token replay, organizational mining, time perspective.