All Outputs (2)

Estimating defection in subscription-type markets with down-sampled representation: Analysis from the scholarly publishing industry (2023)
Working Paper
Roberts, M., Deza, I., Ihshaish, H., & Zhu, Y. Estimating defection in subscription-type markets with down-sampled representation: Analysis from the scholarly publishing industry

We explore the subscription-type market within the context of customer churn, and provide analysis on the business model of such markets, and how these characterise the academic publishing business. The proposed method attempts to provide inference o... Read More about Estimating defection in subscription-type markets with down-sampled representation: Analysis from the scholarly publishing industry.

Maintenance automation using deep learning methods: A case study from the aerospace industry (2023)
Conference Proceeding
Mayhew, P. J., Ihshaish, H., Deza, I., & Del Amo, A. (2023). Maintenance automation using deep learning methods: A case study from the aerospace industry. In Artificial Neural Networks and Machine Learning – ICANN 2023 (295-307). https://doi.org/10.1007/978-3-031-44204-9_25

In this study, state-of-the-art AI models are employed to classify aerospace maintenance records into categories based on the fault descriptions of avionic components. The classification is performed using short natural language text descriptions pro... Read More about Maintenance automation using deep learning methods: A case study from the aerospace industry.