Applications and Developments in Semantic Process Mining

2020 ◽  
Author(s):  
Kingsley Okoye
Keyword(s):  
Process Mining ◽  
Semantic Process

Semantic process mining: A conceptual application of main tools, framework and model analysis

2020 ◽  
Vol 16 (3) ◽  
pp. 127-147
Author(s):  
Kingsley Okoye
Keyword(s):  
Business Processes ◽  
Process Mining ◽  
Mining Method ◽  
Conceptual Level ◽  
Semantic Reasoning ◽  
Abstract Knowledge ◽  
Semantic Concepts ◽  
Semantic Process ◽  
High Level ◽  
Information Semantics

Semantics has been a major challenge when applying the process mining (PM) technique to real-time business processes. The several theoretical and practical efforts to bridge the semantic gap has spanned the advanced notion of the semantic-based process mining (SPM). Fundamentally, the SPM devotes its methods to the idea of making use of existing (semantic) technologies to support the analysis of PM techniques. In principle, the semantic-based process mining method is applied through the acquisition and representation of abstract knowledge about the domain processes in question. To this effect, this paper demonstrates how the semantic concepts and process modelling (reasoning) methods are used to improve the outcomes of PM techniques from the syntactic to a more conceptual level. To do this, the study proposes an SPM-based framework that shows to be intelligent with a high level of semantic reasoning aptitudes. Technically, this paper introduces a process mining approach that uses information (semantics) about different activities that can be found in any given process to make inferences and generate rules or patterns through the method for annotation, semantic reasoning, and conceptual assertions. In turn, the method is theoretically applied to enrich the informative values of the resultant models. Also, the study conducts and systematically reviews the current tools and methods that are used to support the outcomes of the process mining as well as evaluates the results of the different methods to determine the levels of impact and its implications for process mining.

The Proposition of a Framework for Semantic Process Mining

2014 ◽  
Vol 1051 ◽  
pp. 995-999
Author(s):  
Yong Xin Liao ◽  
Eduardo Rocha Loures ◽  
Eduardo Alves Portela Santos ◽  
Osiris Canciglieri
Keyword(s):  
General Framework ◽  
Business Process Management ◽  
Process Management ◽  
Process Mining ◽  
Related Information ◽  
Event Logs ◽  
Semantic Mining ◽  
Semantic Models ◽  
Footprint Analysis ◽  
Semantic Process

As one of the hot topics in Business Process Management (BPM), process mining aims at constructing models to explain what is actually happening from different perspectives based on the process-related information that automatically extracted from event logs. Because the semantics of the data that recorded in event logs are not usually explicit, current mining approaches are somewhat limited. A number of studies have been carried out in the combination use of formalized semantic models and process mining technologies to obtain the semantic mining capability. However, among these researches, there is lack of a guideline that can clearly illustrate different stages during the semantic process mining. The objective of this study is to present a general framework, which unambiguously expresses the main stages of the semantic process mining. Based on this framework, an example about carbon footprint analysis is used to show the possibility of obtaining advantages from semantic process mining.

Associating event logs with ontologies for semantic process mining and analysis

2015 ◽  
Author(s):  
Ossi Nykänen ◽  
Alejandro Rivero-Rodriguez ◽  
Paolo Pileggi ◽  
Pekka A. Ranta ◽  
Meri Kailanto ◽  
...  
Keyword(s):  
Process Mining ◽  
Event Logs ◽  
Semantic Process

Knowledge-Based Trace Abstraction for Semantic Process Mining

2017 ◽  
pp. 267-271 ◽  
Author(s):  
Stefania Montani ◽  
Manuel Striani ◽  
Silvana Quaglini ◽  
Anna Cavallini ◽  
Giorgio Leonardi
Keyword(s):  
Process Mining ◽  
Knowledge Based ◽  
Semantic Process

scholarly journals Hospital Management Based On Semantic Process Mining: A Systematic Review

2019 ◽  
Vol 8 (1) ◽  
pp. 4 ◽  
Author(s):  
Majid Jangi ◽  
Fateme Moghbeli ◽  
Mahya Ghaffari ◽  
Alireza Vahedinemani
Keyword(s):  
Systematic Review ◽  
Business Process ◽  
Process Mining ◽  
Google Scholar ◽  
Extension Field ◽  
Exclusion Criteria ◽  
Event Logs ◽  
Business Process Mining ◽  
Improve Hospital ◽  
Semantic Process

Introduction: Semantic Process Mining is the extension field of process mining that is based on getting knowledge of conceptual event logs (based on ontologies) for analyzing frequent and rare processes. In the healthcare studies, semantic process mining has been used in different hospitals in order to improve processes.Material and Methods: A review of the usages of semantic process mining in hospitals is done. This review contains 65 articles from PubMed, dblp and Google scholar. It is searched from 2000 to 2017. One of them was duplicated and finally, we received 64 articles. Data were extracted according to PRISMA guidelines.Results: Out of 64 articles, 6 of them were related with inclusion and exclusion criteria. Most of them detect business process mining. In 80% of studies, the semantic process mining was useful and effective to improve hospital processes and improve its management.Conclusion: This review can show an overview the application of process mining in hospitals. It can help researchers to compare semantic process mining with other methods for improving processes in hospitals and finally, it shows the use of semantic process mining to enhance hospitals processes.

Process Mining With Semantics

2020 ◽  
pp. 181-216
Keyword(s):  
Real Time ◽  
Business Process ◽  
Process Mining ◽  
Task Force ◽  
Process Modelling ◽  
Business Process Modelling ◽  
Process Discovery ◽  
The Individual ◽  
Semantic Process

This chapter contains the application of the semantic process mining approach in real-time. This includes the series of analysis that were performed not only to show how the method is applied in different scenarios or settings for process mining purposes, but also how to technically apply the method for semantic process mining tasks. In the first section, the work shows how the authors practically apply the current tools that supports the process mining through its participation in the Process Discovery Contest organised by the IEEE CIS Task Force on Process Mining. In the second section, the chapter shows how it expounds the results and amalgamation of the two process mining techniques, namely fuzzy miner and business process modelling notation (BPMN) approach, in order to demonstrate the capability of the proposed semantic-based fuzzy miner being able to perform a more conceptual and accurate classification of the individual traces within the process or input models.

Semantic Business Process Mining of SAP Transactions

2010 ◽  
pp. 416-429
Author(s):  
Jon Espen Ingvaldsen ◽  
Jon Atle Gulla
Keyword(s):  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Process Mining ◽  
Structured Data ◽  
The Core ◽  
Management Perspective ◽  
System Logs ◽  
Business Process Mining ◽  
Semantic Process

This chapter introduces semantic business process mining of SAP transaction logs. SAP systems are promising domains for semantic process mining as they contain transaction logs that are linked to large amounts of structured data. A challenge with process mining these transaction logs is that the core of SAP systems was not originally designed from the business process management perspective. The business process layer was added later without full rearrangement of the system. As a result, system logs produced by SAP are not process-based, but transaction-based. This means that the system does not produce traces of process instances that are needed for process mining. In this chapter, we show how data available in SAP systems can enrich process instance logs with ontologically structured concepts, and evaluate techniques for mapping executed transaction sequences with predefined process hierarchies.

Semantic Business Process Mining of SAP Transactions

2011 ◽  
pp. 866-878 ◽  
Author(s):  
Jon Espen Ingvaldsen ◽  
Jon Atle Gulla
Keyword(s):  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Process Mining ◽  
Structured Data ◽  
The Core ◽  
Management Perspective ◽  
System Logs ◽  
Business Process Mining ◽  
Semantic Process

This chapter introduces semantic business process mining of SAP transaction logs. SAP systems are promising domains for semantic process mining as they contain transaction logs that are linked to large amounts of structured data. A challenge with process mining these transaction logs is that the core of SAP systems was not originally designed from the business process management perspective. The business process layer was added later without full rearrangement of the system. As a result, system logs produced by SAP are not process-based, but transaction-based. This means that the system does not produce traces of process instances that are needed for process mining. In this chapter, we show how data available in SAP systems can enrich process instance logs with ontologically structured concepts, and evaluate techniques for mapping executed transaction sequences with predefined process hierarchies.

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