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All Outputs (3)

Blockchain and artificial intelligence – Managing a secure and sustainable supply chain (2021)
Book Chapter
Pimenidis, E., Patsavellas, J., & Tonkin, M. (2021). Blockchain and artificial intelligence – Managing a secure and sustainable supply chain. In H. Jahankhani, A. Jamal, & S. Lawson (Eds.), Cybersecurity, Privacy and Freedom Protection in the Connected World. (1). Springer. https://doi.org/10.1007/978-3-030-68534-8

Supply chain management is often the most challenging part of any business that manufactures, sells goods, or provides services. Regardless of whether the operations are mostly physical or online, managing supply chains largely relies on being able t... Read More about Blockchain and artificial intelligence – Managing a secure and sustainable supply chain.

An approach for web service selection and dynamic composition based on linked open data (2018)
Book Chapter
Vesyropoulos, N., Georgiadis, C., & Pimenidis, E. (2018). An approach for web service selection and dynamic composition based on linked open data. In N. T. Nguyen, & R. Kowalczyk (Eds.), Transactions on Computational Collective Intelligence XXX (54-70). Springer. https://doi.org/10.1007/978-3-319-99810-7_3

The wide adoption of the Service Oriented Architecture (SOA) paradigm has provided a means for heterogeneous systems to seamlessly interact and exchange data. Thus, enterprises and end-users have widely utilized Web Services (WS), either as stand-alo... Read More about An approach for web service selection and dynamic composition based on linked open data.

Reproduction of experiments in recommender systems evaluation based on explanations (2018)
Book Chapter
Polatidis, N., & Pimenidis, E. (2018). Reproduction of experiments in recommender systems evaluation based on explanations. In E. Pimenidis, & C. Jayne (Eds.), Engineering Applications of Neural Networks. Switzerland: Springer International Publishing AG. https://doi.org/10.1007/978-3-319-98204-5

The offline evaluation of recommender systems is typically based on accuracy metrics such as the Mean Absolute Error (MAE) and the Root Mean Squared Error (RMSE), while on the other hand Precision and Recall is used to measure the quality of the top-... Read More about Reproduction of experiments in recommender systems evaluation based on explanations.