A technique for determining relevance scores of process activities using graph-based neural networks Article Swipe

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Matthias Stierle , Sven Weinzierl , Maximilian Harl , Martin Matzner ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.1016/j.dss.2021.113511

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Relevance (law) Computer science Process (computing) Process mining Graph Process modeling Business process Business process discovery Data science Data mining Business process modeling Machine learning Artificial intelligence Process management Work in process Theoretical computer science Engineering Operations management Law Operating system Political science

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Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.dss.2021.113511
OA Status: hybrid
Cited By: 20
References: 53
Related Works: 10
OpenAlex ID: https://openalex.org/W3048310814

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DOI: https://doi.org/10.1016/j.dss.2021.113511

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Title: A technique for determining relevance scores of process activities using graph-based neural networks

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Language: en

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Publication year: 2021

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Publication date: 2021-02-04

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Authors: Matthias Stierle, Sven Weinzierl, Maximilian Harl, Martin Matzner

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Landing page: https://doi.org/10.1016/j.dss.2021.113511

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Concepts: Relevance (law), Computer science, Process (computing), Process mining, Graph, Process modeling, Business process, Business process discovery, Data science, Data mining, Business process modeling, Machine learning, Artificial intelligence, Process management, Work in process, Theoretical computer science, Engineering, Operations management, Law, Operating system, Political science

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Cited by: 20

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referenced_works_count	53
abstract_inverted_index
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countries_distinct_count	1
institutions_distinct_count	4
corresponding_institution_ids	https://openalex.org/I181369854
sustainable_development_goals[0].id	https://metadata.un.org/sdg/9
sustainable_development_goals[0].score	0.4399999976158142
sustainable_development_goals[0].display_name	Industry, innovation and infrastructure
citation_normalized_percentile.value	0.9172601
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True