Search Results - subject:"Unsupervised"

Identifying weak signals in the labor market : a machine learning approach for strategic policymaking

Kanzola, Anna-Maria; Papaioannou, Konstantina; … - In: Journal of innovation & knowledge : JIK 11 (2026), pp. 1-9

This study introduces a novel machine learning-based methodology for detecting and forecasting the strength of weak signals in the labor market, using Greece as a case study and utilizing Eurostat time series data (2000-2023). Weak signals, conceptualized as subtle anomalies within otherwise...

Persistent link: https://www.econbiz.de/10015607728

Choosing product space : lessons from the app economy

Jamison, Mark A.; Yu, Byoungmin - 2026

leverage natural language processing and unsupervised machine learning to cluster apps using pairwise cosine similarity, which …

Persistent link: https://www.econbiz.de/10015571954

Unsupervised machine learning-based financial anomalies, ESG, and accounting conservatism

Prawat Benyasrisawat; Pakawat Kuboonya-arags - In: International Journal of Financial Studies : open … 14 (2026) 5, pp. 1-18

unsupervised machine learning to identify reporting anomalies for firms. Our findings suggest that higher financial anomaly risk is …

Persistent link: https://www.econbiz.de/10015652368

Surprisal-based algorithm for detecting anomalies in categorical data

Cherkaoui, Ossama; Anoun, Houda; Maizate, Abderrahim - In: Data science and management : DSM 8 (2025) 2, pp. 185-195

Anomaly detection is an important research area in a diverse range of real-world applications. Although many algorithms have been proposed to address anomaly detection for numerical datasets, categorical and mixed datasets remain a significant challenge, primarily because a natural distance...

Persistent link: https://www.econbiz.de/10015455584

Targeting audience personas with programmatic geographic segments using unsupervised methods

Noorithaya, Viraj - In: IIMB Management Review 37 (2025) 1, pp. 2-14

The digital advertising industry, where clients advertise to existing and potential customers through digital channels, is going through a rapid transformation. This is necessitated by evolving privacy laws such as General Data Protection Regulation (GDPR) and California Consumer Privacy Act...

Persistent link: https://www.econbiz.de/10015444172

Assessing driving risk through unsupervised detection of anomalies in telematics time series data

Chan, Ian Weng; Badescu, Andrei L.; Lin, X. Sheldon - In: ASTIN bulletin : the journal of the International … 55 (2025) 2, pp. 205-241

Persistent link: https://www.econbiz.de/10015450030

A review on unsupervised learning algorithms and applications in supply chain management

Rolf, Benjamin; Beier, Alexander; Jackson, Ilya; … - In: International journal of production research 63 (2025) 5, pp. 1933-1983

Persistent link: https://www.econbiz.de/10015421584

Padrões de inovação na indústria de transformação brasileira : uma análise exploratória a partir de dados da PINTEC Semestral 2021

Vargas, Marco Antonio; Macharete, Rafael Ribeiro; … - In: Estudos econômicos 55 (2025) 2, pp. 1-37

Persistent link: https://www.econbiz.de/10015632822

Unsupervised machine learning based anomaly detection in high frequency data : Evidence from Cryptocurrency Market

Latif, Muhammad Nouman; Kaplan, Muhittin; Khan, Asad ul … - In: Pakistan journal of commerce and social sciences 19 (2025) 3, pp. 407-440

cryptocurrency markets using Jupyter Notebook. We compare four advanced unsupervised machine learning models, i.e, Density …-known cryptocurrencies at three different temporal resolutions (daily, hourly, and 15-minute) the performance of these four unsupervised … across the three unsupervised learning methods. Number of anomalies also depends on the volatility and time interval of …

Persistent link: https://www.econbiz.de/10015475249

Using archetypal analysis to derive a typology of knowledge networks in European bioclusters

Abbasiharofteh, Milad; Hermans, Frans - In: Regional Studies 59 (2025) 1, pp. 1-17

The shift to a bioeconomy necessitates radical innovations to move from a fossil- to a bio-based economy, with bioclusters playing a crucial role by fostering collaboration among a wide range of co-located actors to find solutions. Through a novel methodological approach in regional studies...

Persistent link: https://www.econbiz.de/10015375287