Comparing and Aligning Process Representations

Aa, Han van der

doi:10.1007/978-3-319-94634-4

Cited by 3 publications

(1 citation statement)

References 194 publications

(369 reference statements)

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“…Other close works focus on the automatic comparison and alignment of process information in semi-structured and unstructured formats [21]. Henrik et al [22] proposed a process querying technique that can search repositories of both textual and model-based process descriptions.…”

Section: Related Workmentioning

confidence: 99%

A Machine Translation Like Approach to Generate Business Process Model from Textual Description

2023

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Modeling is one of the core tasks in Business Process Management (BPM). It represents the most critical step in the BPM life cycle and is considered as a time consuming and costly task. These challenges raised the question of how researchers can save this cost by building tools that could support modeling experts in their work to reduce the manual workload. In this paper, we propose a Machine Translation (MT) like approach to deal with the problem of generating a business process model based on a textual description. We chose to follow a semantic transfer-based MT approach. Our approach consists of two main phases: The natural Language Analysis phase and BPMN diagram generation. Natural Language Analysis phase aims to analyze the text and extract the required knowledge. One of the main outputs for this phase is a Concept Map which summarizes the concepts of the related domain and the relationships between these concepts. This map represents a background for our processing in the second phase where we try to generate the "translation", which is the BPMN diagram in our case. We achieve our goal in the second phase via a set of semantic, syntactic, and morphological manipulations. The approach has been implemented and evaluated usinga similarity metric based on the Graph Edit Distance. The results show that the proposed approach was able to generate models that are more than 81% similar to those created manually by a human, outperforming the state of the art in this topic .

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Section: Related Workmentioning

confidence: 99%

A Machine Translation Like Approach to Generate Business Process Model from Textual Description

2023

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Complex Event Processing Methods for Process Querying

Artikis

Weidlich

2021

Process Querying Methods

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A Machine Translation Like Approach to Generate Business Process Model From Textual Description

Sonbol

Rebdawi

Ghneim

2022

Preprint

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Modeling is one of the core tasks in Business Process Management (BPM). It represents the most critical step in the BPM life cycle and is considered as a time consuming and costly task. These challenges raised the question of how researchers can save this cost by building tools that could support modeling experts in their work to reduce the manual workload. In this paper, we propose a Machine Translation (MT) like approach to deal with the problem of generating a business process model based on a textual description. We chose to follow a semantic transfer-based MT approach. Our approach consists of two main phases: The natural Language Analysis phase and BPMN diagram generation. Natural Language Analysis phase aims to analyze the text and extract the required knowledge. One of the main outputs for this phase is a Concept Map which summarizes the concepts of the related domain and the relationships between these concepts. This map represents a background for our processing in the second phase where we try to generate the "translation", which is the BPMN diagram in our case. We achieve our goal in the second phase via a set of semantic, syntactic, and morphological manipulations. The approach has been implemented and evaluated using a similarity metric based on the Graph Edit Distance. The results show that the proposed approach was able to generate models that are more than 81% similar to those created manually by a human, outperforming the state of the art in this topic.

show abstract

Comparing and Aligning Process Representations

Cited by 3 publications

References 194 publications

A Machine Translation Like Approach to Generate Business Process Model from Textual Description

A Machine Translation Like Approach to Generate Business Process Model from Textual Description

Complex Event Processing Methods for Process Querying

A Machine Translation Like Approach to Generate Business Process Model From Textual Description

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