PUBLIKATIONSSERVER

Nico Migenda

https://orcid.org/0000-0002-7223-1735

18 Publikationen

Alle markieren

[18]
2026 | Artikel | FH-PUB-ID: 6485 | OA
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: H-NGPCA: Hierarchical clustering of data streams with adaptive number of clusters and adaptive dimensionality. In: PLOS One Bd. 21, Public Library of Science (PLoS) (2026), Nr. 1
HSBI-PUB | DOI | Download (ext.)
 
[17]
2025 | Artikel | FH-PUB-ID: 6244 | OA
Niederhaus, Marvin ; Migenda, Nico ; Weller, Julian ; Kohlhase, Martin ; Schenck, Wolfram: Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems. In: Big Data and Cognitive Computing Bd. 9, MDPI AG (2025), Nr. 10
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[16]
2025 | Datenpublikation | FH-PUB-ID: 6486
Migenda, Nico: Clustering in High-Dimensional Data Streams with Adaptive Local Principal Component Analysis : Universität Bielefeld, 2025
HSBI-PUB | DOI
 
[15]
2024 | Konferenzbeitrag | FH-PUB-ID: 4916
Weller, Julian ; Migenda, Nico ; Kühn, Arno ; Dumitrescu, Roman: Prescriptive Analytics Data Canvas: Strategic Planning For Prescriptive Analytics In Smart Factories. In:  : Hannover : publish-Ing., 2024
HSBI-PUB | DOI
 
[14]
2024 | Artikel | FH-PUB-ID: 5497
Weller, Julian ; Migenda, Nico ; Enzberg, Sebastian von ; Kohlhase, Martin ; Schenck, Wolfram ; Dumitrescu, Roman: Design decisions for integrating Prescriptive Analytics Use Cases into Smart Factories. In: Procedia CIRP Bd. 128, Elsevier BV (2024), S. 424–429
HSBI-PUB | DOI
 
[13]
2024 | Artikel | FH-PUB-ID: 4050
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: Adaptive local Principal Component Analysis improves the clustering of high-dimensional data. In: Pattern Recognition Bd. 146, Elsevier BV (2024)
HSBI-PUB | DOI
 
[12]
2024 | Artikel | FH-PUB-ID: 4698
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: NGPCA: Clustering of high-dimensional and non-stationary data streams. In: Software Impacts Bd. 20, Elsevier BV (2024)
HSBI-PUB | DOI
 
[11]
2024 | Konferenzbeitrag | FH-PUB-ID: 4699
Niederhaus, Marvin ; Migenda, Nico ; Weller, Julian ; Schenck, Wolfram ; Kohlhase, Martin: Technical Readiness of Prescriptive Analytics Platforms: A Survey. In: IEEE (Hrsg.): 2024 35th Conference of Open Innovations Association (FRUCT) : IEEE, 2024, S. 509–519
HSBI-PUB | DOI
 
[10]
2024 | Buchbeitrag | FH-PUB-ID: 4915
Weller, Julian ; Migenda, Nico ; Liu, Rui ; Wegel, Arthur ; von Enzberg, Sebastian ; Kohlhase, Martin ; Schenck, Wolfram ; Dumitrescu, Roman: Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories. In: Niggemann, O. ; Beyerer, J. ; Krantz, M. ; Kühnert, C. (Hrsg.): Machine Learning for Cyber-Physical Systems. Selected papers from the International Conference ML4CPS 2023, Technologien für die intelligente Automation. Bd. 18. Cham : Springer Nature Switzerland, 2024, S. 89–100
HSBI-PUB | DOI
 
[9]
2024 | Artikel | FH-PUB-ID: 4913
Weller, Julian ; Migenda, Nico ; Naik, Yash ; Heuwinkel, Tim ; Kühn, Arno ; Kohlhase, Martin ; Schenck, Wolfram ; Dumitrescu, Roman: Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories. In: Mathematics Bd. 12, MDPI AG (2024), Nr. 17
HSBI-PUB | DOI
 
[8]
2023 | Konferenzbeitrag | FH-PUB-ID: 4700
Weller, Julian ; Migenda, Nico ; Wegel, Arthur ; Kohlhase, Martin ; Schenck, Wolfram ; Dumitrescu, Roman: Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories. In: IEEE (Hrsg.): 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS) : IEEE, 2023, S. 1–7
HSBI-PUB | DOI
 
[7]
2022 | Konferenzbeitrag | FH-PUB-ID: 2569
Hoppe, Christoph ; Migenda, Nico ; Pelkmann, David ; Hötte, Daniel Antonius ; Schenck, Wolfram: Collaborative System for Question Answering in German Case Law Documents. In: Camarinha-Matos, L. M. ; Ortiz, A. ; Boucher, X. ; Osório, A. L. (Hrsg.): Collaborative Networks in Digitalization and Society 5.0, IFIP Advances in Information and Communication Technology. Cham : Springer International Publishing, 2022, S. 303–312
HSBI-PUB | DOI
 
[6]
2021 | Konferenzbeitrag | FH-PUB-ID: 2570
Hoppe, Christoph ; Pelkmann, David ; Migenda, Nico ; Hotte, Daniel Antonius ; Schenck, Wolfram: Towards Intelligent Legal Advisors for Document Retrieval and Question-Answering in German Legal Documents. In: 2021 IEEE Fourth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE) : IEEE, 2021, S. 29–32
HSBI-PUB | DOI
 
[5]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Voigt, Tim ; Migenda, Nico ; Schöne, Marvin ; Pelkmann, David ; Fricke, Matthias ; Schenck, Wolfram ; Kohlhase, Martin: Advanced Data Analytics Platform for Manufacturing Companies. In: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) : IEEE, 2021, S. 01–08
HSBI-PUB | DOI
 
[4]
2021 | Konferenzbeitrag | FH-PUB-ID: 2572
Steinmann, Luca ; Migenda, Nico ; Voigt, Tim ; Kohlhase, Martin ; Schenck, Wolfram: Variational Autoencoder based Novelty Detection for Real-World Time Series. In: 2021 3rd International Conference on Management Science and Industrial Engineering. New York, NY, USA : ACM, 2021, S. 1–7
HSBI-PUB | DOI
 
[3]
2021 | Artikel | FH-PUB-ID: 1203
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: Adaptive dimensionality reduction for neural network-based online principal component analysis. In: PLOS ONE Bd. 16, Public Library of Science (PLoS) (2021), Nr. 3
HSBI-PUB | DOI
 
[2]
2020 | Konferenzbeitrag | FH-PUB-ID: 2574
Migenda, Nico ; Schenck, Wolfram: Adaptive Dimensionality Reduction for Local Principal Component Analysis. In: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) : IEEE, 2020, S. 1579–1586
HSBI-PUB | DOI
 
[1]
2019 | Buchbeitrag | FH-PUB-ID: 1208
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: Adaptive Dimensionality Adjustment for Online “Principal Component Analysis”. In: Yin, H. ; Camacho, D. ; Tino, P. ; Tallón-Ballesteros, A. J. ; Menezes, R. ; Allmendinger, R. (Hrsg.): Intelligent Data Engineering and Automated Learning – IDEAL 2019. 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I, Lecture Notes in Computer Science. Cham : Springer International Publishing, 2019, S. 76–84
HSBI-PUB | DOI
 
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Zitationsstil: DIN 1505

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18 Publikationen

Alle markieren

[18]
2026 | Artikel | FH-PUB-ID: 6485 | OA
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: H-NGPCA: Hierarchical clustering of data streams with adaptive number of clusters and adaptive dimensionality. In: PLOS One Bd. 21, Public Library of Science (PLoS) (2026), Nr. 1
HSBI-PUB | DOI | Download (ext.)
 
[17]
2025 | Artikel | FH-PUB-ID: 6244 | OA
Niederhaus, Marvin ; Migenda, Nico ; Weller, Julian ; Kohlhase, Martin ; Schenck, Wolfram: Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems. In: Big Data and Cognitive Computing Bd. 9, MDPI AG (2025), Nr. 10
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[16]
2025 | Datenpublikation | FH-PUB-ID: 6486
Migenda, Nico: Clustering in High-Dimensional Data Streams with Adaptive Local Principal Component Analysis : Universität Bielefeld, 2025
HSBI-PUB | DOI
 
[15]
2024 | Konferenzbeitrag | FH-PUB-ID: 4916
Weller, Julian ; Migenda, Nico ; Kühn, Arno ; Dumitrescu, Roman: Prescriptive Analytics Data Canvas: Strategic Planning For Prescriptive Analytics In Smart Factories. In:  : Hannover : publish-Ing., 2024
HSBI-PUB | DOI
 
[14]
2024 | Artikel | FH-PUB-ID: 5497
Weller, Julian ; Migenda, Nico ; Enzberg, Sebastian von ; Kohlhase, Martin ; Schenck, Wolfram ; Dumitrescu, Roman: Design decisions for integrating Prescriptive Analytics Use Cases into Smart Factories. In: Procedia CIRP Bd. 128, Elsevier BV (2024), S. 424–429
HSBI-PUB | DOI
 
[13]
2024 | Artikel | FH-PUB-ID: 4050
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: Adaptive local Principal Component Analysis improves the clustering of high-dimensional data. In: Pattern Recognition Bd. 146, Elsevier BV (2024)
HSBI-PUB | DOI
 
[12]
2024 | Artikel | FH-PUB-ID: 4698
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: NGPCA: Clustering of high-dimensional and non-stationary data streams. In: Software Impacts Bd. 20, Elsevier BV (2024)
HSBI-PUB | DOI
 
[11]
2024 | Konferenzbeitrag | FH-PUB-ID: 4699
Niederhaus, Marvin ; Migenda, Nico ; Weller, Julian ; Schenck, Wolfram ; Kohlhase, Martin: Technical Readiness of Prescriptive Analytics Platforms: A Survey. In: IEEE (Hrsg.): 2024 35th Conference of Open Innovations Association (FRUCT) : IEEE, 2024, S. 509–519
HSBI-PUB | DOI
 
[10]
2024 | Buchbeitrag | FH-PUB-ID: 4915
Weller, Julian ; Migenda, Nico ; Liu, Rui ; Wegel, Arthur ; von Enzberg, Sebastian ; Kohlhase, Martin ; Schenck, Wolfram ; Dumitrescu, Roman: Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories. In: Niggemann, O. ; Beyerer, J. ; Krantz, M. ; Kühnert, C. (Hrsg.): Machine Learning for Cyber-Physical Systems. Selected papers from the International Conference ML4CPS 2023, Technologien für die intelligente Automation. Bd. 18. Cham : Springer Nature Switzerland, 2024, S. 89–100
HSBI-PUB | DOI
 
[9]
2024 | Artikel | FH-PUB-ID: 4913
Weller, Julian ; Migenda, Nico ; Naik, Yash ; Heuwinkel, Tim ; Kühn, Arno ; Kohlhase, Martin ; Schenck, Wolfram ; Dumitrescu, Roman: Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories. In: Mathematics Bd. 12, MDPI AG (2024), Nr. 17
HSBI-PUB | DOI
 
[8]
2023 | Konferenzbeitrag | FH-PUB-ID: 4700
Weller, Julian ; Migenda, Nico ; Wegel, Arthur ; Kohlhase, Martin ; Schenck, Wolfram ; Dumitrescu, Roman: Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories. In: IEEE (Hrsg.): 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS) : IEEE, 2023, S. 1–7
HSBI-PUB | DOI
 
[7]
2022 | Konferenzbeitrag | FH-PUB-ID: 2569
Hoppe, Christoph ; Migenda, Nico ; Pelkmann, David ; Hötte, Daniel Antonius ; Schenck, Wolfram: Collaborative System for Question Answering in German Case Law Documents. In: Camarinha-Matos, L. M. ; Ortiz, A. ; Boucher, X. ; Osório, A. L. (Hrsg.): Collaborative Networks in Digitalization and Society 5.0, IFIP Advances in Information and Communication Technology. Cham : Springer International Publishing, 2022, S. 303–312
HSBI-PUB | DOI
 
[6]
2021 | Konferenzbeitrag | FH-PUB-ID: 2570
Hoppe, Christoph ; Pelkmann, David ; Migenda, Nico ; Hotte, Daniel Antonius ; Schenck, Wolfram: Towards Intelligent Legal Advisors for Document Retrieval and Question-Answering in German Legal Documents. In: 2021 IEEE Fourth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE) : IEEE, 2021, S. 29–32
HSBI-PUB | DOI
 
[5]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Voigt, Tim ; Migenda, Nico ; Schöne, Marvin ; Pelkmann, David ; Fricke, Matthias ; Schenck, Wolfram ; Kohlhase, Martin: Advanced Data Analytics Platform for Manufacturing Companies. In: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) : IEEE, 2021, S. 01–08
HSBI-PUB | DOI
 
[4]
2021 | Konferenzbeitrag | FH-PUB-ID: 2572
Steinmann, Luca ; Migenda, Nico ; Voigt, Tim ; Kohlhase, Martin ; Schenck, Wolfram: Variational Autoencoder based Novelty Detection for Real-World Time Series. In: 2021 3rd International Conference on Management Science and Industrial Engineering. New York, NY, USA : ACM, 2021, S. 1–7
HSBI-PUB | DOI
 
[3]
2021 | Artikel | FH-PUB-ID: 1203
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: Adaptive dimensionality reduction for neural network-based online principal component analysis. In: PLOS ONE Bd. 16, Public Library of Science (PLoS) (2021), Nr. 3
HSBI-PUB | DOI
 
[2]
2020 | Konferenzbeitrag | FH-PUB-ID: 2574
Migenda, Nico ; Schenck, Wolfram: Adaptive Dimensionality Reduction for Local Principal Component Analysis. In: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) : IEEE, 2020, S. 1579–1586
HSBI-PUB | DOI
 
[1]
2019 | Buchbeitrag | FH-PUB-ID: 1208
Migenda, Nico ; Möller, Ralf ; Schenck, Wolfram: Adaptive Dimensionality Adjustment for Online “Principal Component Analysis”. In: Yin, H. ; Camacho, D. ; Tino, P. ; Tallón-Ballesteros, A. J. ; Menezes, R. ; Allmendinger, R. (Hrsg.): Intelligent Data Engineering and Automated Learning – IDEAL 2019. 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I, Lecture Notes in Computer Science. Cham : Springer International Publishing, 2019, S. 76–84
HSBI-PUB | DOI
 
Markierte Publikation(en)

Suche

Publikationen filtern

Darstellung / Sortierung

Zitationsstil: DIN 1505

Export / Einbettung