Toward new data for IT and IoT project management method prediction Article Swipe
Soukaina Merzouk
,
R. Gandoul
,
Abdelaziz Marzak
,
Nawal Sael
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.23939/mmc2023.02.557
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.23939/mmc2023.02.557
Selecting the best project management method at the workplace helps to deliver a high-quality product to the customer. Hence, the need for good knowledge of management methods, their characteristics, advantages, and disadvantages, is necessary to be able to select the best for the specific project. However, until now, no large dataset for Machine Learning and decision-making model, model or system has been proposed to help project managers to the most efficient method adapted to the constraints of their projects. This work develops the construction of the dataset for agile and IoT project management method based on the real experiences. In this paper, our objective is to propose a criteria-based model that allows the choice of the best management method to adopt for such an IT or IoT project according to a set of criteria.
Related Topics
Concepts
Computer science
Agile software development
Project management
Set (abstract data type)
Work (physics)
Project management triangle
Best practice
Quality (philosophy)
Internet of Things
Process management
Engineering management
Knowledge management
Data science
Software engineering
Systems engineering
Engineering
World Wide Web
Philosophy
Epistemology
Programming language
Economics
Mechanical engineering
Management
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.23939/mmc2023.02.557
- https://science.lpnu.ua/sites/default/files/journal-paper/2023/may/30369/2023102557565.pdf
- OA Status
- bronze
- Cited By
- 6
- References
- 9
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4379108762
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4379108762Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.23939/mmc2023.02.557Digital Object Identifier
- Title
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Toward new data for IT and IoT project management method predictionWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
-
Soukaina Merzouk, R. Gandoul, Abdelaziz Marzak, Nawal SaelList of authors in order
- Landing page
-
https://doi.org/10.23939/mmc2023.02.557Publisher landing page
- PDF URL
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https://science.lpnu.ua/sites/default/files/journal-paper/2023/may/30369/2023102557565.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
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bronzeOpen access status per OpenAlex
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https://science.lpnu.ua/sites/default/files/journal-paper/2023/may/30369/2023102557565.pdfDirect OA link when available
- Concepts
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Computer science, Agile software development, Project management, Set (abstract data type), Work (physics), Project management triangle, Best practice, Quality (philosophy), Internet of Things, Process management, Engineering management, Knowledge management, Data science, Software engineering, Systems engineering, Engineering, World Wide Web, Philosophy, Epistemology, Programming language, Economics, Mechanical engineering, ManagementTop concepts (fields/topics) attached by OpenAlex
- Cited by
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6Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 5, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
9Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.model, | 56 |
| abstract_inverted_index.paper, | 101 |
| abstract_inverted_index.select | 38 |
| abstract_inverted_index.system | 59 |
| abstract_inverted_index.Machine | 52 |
| abstract_inverted_index.adapted | 72 |
| abstract_inverted_index.dataset | 50, 86 |
| abstract_inverted_index.deliver | 11 |
| abstract_inverted_index.product | 14 |
| abstract_inverted_index.project | 3, 65, 91, 127 |
| abstract_inverted_index.propose | 106 |
| abstract_inverted_index.However, | 45 |
| abstract_inverted_index.Learning | 53 |
| abstract_inverted_index.develops | 81 |
| abstract_inverted_index.managers | 66 |
| abstract_inverted_index.methods, | 26 |
| abstract_inverted_index.project. | 44 |
| abstract_inverted_index.proposed | 62 |
| abstract_inverted_index.specific | 43 |
| abstract_inverted_index.Selecting | 0 |
| abstract_inverted_index.according | 128 |
| abstract_inverted_index.criteria. | 133 |
| abstract_inverted_index.customer. | 17 |
| abstract_inverted_index.efficient | 70 |
| abstract_inverted_index.knowledge | 23 |
| abstract_inverted_index.necessary | 33 |
| abstract_inverted_index.objective | 103 |
| abstract_inverted_index.projects. | 78 |
| abstract_inverted_index.workplace | 8 |
| abstract_inverted_index.management | 4, 25, 92, 117 |
| abstract_inverted_index.advantages, | 29 |
| abstract_inverted_index.constraints | 75 |
| abstract_inverted_index.construction | 83 |
| abstract_inverted_index.experiences. | 98 |
| abstract_inverted_index.high-quality | 13 |
| abstract_inverted_index.criteria-based | 108 |
| abstract_inverted_index.disadvantages, | 31 |
| abstract_inverted_index.decision-making | 55 |
| abstract_inverted_index.characteristics, | 28 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.90366933 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |