{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:45:18Z","timestamp":1742946318355,"version":"3.40.3"},"publisher-location":"Wiesbaden","reference-count":12,"publisher":"Springer Fachmedien Wiesbaden","isbn-type":[{"type":"print","value":"9783658437046"},{"type":"electronic","value":"9783658437053"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,4,17]],"date-time":"2024-04-17T00:00:00Z","timestamp":1713312000000},"content-version":"vor","delay-in-days":107,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper presents the research project \u201cKI_eeper \u2013 Know-how to keep\u201d and a first technical research. In this project, tacit experiential knowledge of employees is to be recorded and processed by using artificial intelligence to make it available to inexperienced workers due to a digital assistance system.<\/jats:p><jats:p>First, the difference between tacit and explicit knowledge is briefly explained. The existing case studies will then be examined in more detail and it will be explained why artificial intelligence is necessary for a general solution to identify and storage knowledge in this research project.<\/jats:p><jats:p>Subsequently, various machine learning models and algorithms will be considered, which could be used for a potential technical solution.<\/jats:p>","DOI":"10.1007\/978-3-658-43705-3_11","type":"book-chapter","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T11:20:25Z","timestamp":1713266425000},"page":"143-151","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Identification of Machine Learning Algorithms to Share Tacit Experimental Knowledge in Manual Production"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1196-4361","authenticated-orcid":false,"given":"Christian","family":"Prange","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amin","family":"Beikzadeh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9592-872X","authenticated-orcid":false,"given":"Holger","family":"Dander","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicole","family":"Ottersb\u00f6ck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,17]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company. How Japanese companies create the dynamics of innovation \/ Ikujiro Nonaka and Hirotaka Takeuchi. Oxford University Press, Oxford.","DOI":"10.1093\/oso\/9780195092691.001.0001"},{"key":"11_CR2","unstructured":"Neuweg, G. H. (2001). K\u00f6nnerschaft und implizites Wissen: zur lehr-lerntheoretischen Bedeutung der Erkenntnis- und Wissenstheorie Michael Polanys. Waxmann, M\u00fcnster."},{"key":"11_CR3","unstructured":"Implizites Wissen im Unternehmen. (2023). http:\/\/www.implizites-mitarbeiterwissen.de\/implizites-mitarbeiterwissen\/ (date of retrieval 03.04.2023)."},{"key":"11_CR4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-658-11643-9","volume-title":"Wissensorientierte Unternehmensf\u00fchrung","author":"K North","year":"2016","unstructured":"North, K. (2016). Wissensorientierte Unternehmensf\u00fchrung. Wiesbaden: Wissensmanagement gestalten \/ Klaus North. Springer Gabler."},{"key":"11_CR5","unstructured":"Diedering, R. (2018). Wissensmanagement. Faktoren zum Erhalt des Wissens einer Organisation vor dem Hintergrund des demographischen Wandels. GRIN Verlag."},{"key":"11_CR6","unstructured":"INTERNATIONAL ATOMIC ENERGY AGENCY (2022). Mentoring and Coaching for Knowledge Management in Nuclear Organizations, IAEA-TECDOC-1999, IAEA, Vienna. https:\/\/www.iaea.org\/publications\/15089\/mentoring-and-coaching-for-knowledge-management-in-nuclear-organizations."},{"key":"11_CR7","unstructured":"Hardege, S. (2023). DIHK-Fachkr\u00e4ftereport 2022."},{"key":"11_CR8","unstructured":"Ottersb\u00f6ck, N., Dander, H., Prange, C., Peters, S., & Ochterbeck, J. (2023). Flexibler Arbeitskr\u00e4fteeinsatz durch KI-basierten Wissenstransfer. Praxisbericht aus dem Forschungsprojekt KI_eeper \u2013 Know how to keep. WERKWANDEL."},{"key":"11_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108192","volume":"120","author":"Z Yang","year":"2021","unstructured":"Yang, Z., Zhang, A., & Sudjianto, A. (2021). GAMI-Net: An explainable neural network based on generalized additive models with structured interactions. Pattern Recognition, 120, 108192. https:\/\/doi.org\/10.1016\/j.patcog.2021.108192","journal-title":"Pattern Recognition"},{"key":"11_CR10","unstructured":"Huang X., Jensen J. (1997). A machine-learning approach to automated knowledge-base building for remote sensing image analysis with GIS data. Photogrammetric Engineering & Remote Sensing, 63(10), 1185\u20131194."},{"key":"11_CR11","doi-asserted-by":"publisher","unstructured":"Letham, B., Rudin, C., McCormick, T. H., & Madigan, D. (2015). Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model. The Annals of Applied Statistics, 9. https:\/\/doi.org\/10.1214\/15-AOAS848.","DOI":"10.1214\/15-AOAS848."},{"key":"11_CR12","doi-asserted-by":"publisher","unstructured":"Li, O., Liu, H., Chen, C., & Rudin, C. (2018). 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