· Dietmar Jannach1 Received: 28 December 2022 / Accepted in revised form: 27 July 2023 / Published online: 6 October 2023 © The Author(s) 2023 Abstract Session-based recommender systems model the interests o
Finally, the application of this model is illustrated through a case study of a notebook computer product for cost estimation and the results show that its efficiency and effectiveness in solving the cost estimation problem of plastic injection products at the development stage. 展开 关键词: ...
The developed taxonomy that involves feature tolerance relationships is at the core of the information data model utilised by the original algorithm which was aimed at generic process sequencing for the definite category of mechanical parts. Through the developed algorithm, adequate process alternatives ...
Although hybrid-learning architectures have achieved fairly promising performance, especially on large datasets, it easily tends to overfit because of a huge number of model parameters but few samples of Kla sites. This phenomenon is common for many deep learning-based architectures in such a ...
To examine the advantages of object-based and feature-based approaches, we simulated this task using two different model learners. The object-based learner directly estimates the reward values of individual objects via reward feedback, whereas the feature-based learner estimates the reward values of ...
The proposed method exhibits high inference speed owing to an efficient computation-based lightweight model that uses few trainable parameters that allows the model to be used in real-time applications. The proposed method exhibits excellent generalizability and performance in limited, small-scale, and...
The digital transformation of manufacturing requires digitalization, including automatic and efficient data exchange. Model-based definitions (MBDs) captur
The shape space is defined by a 2D Modified Active Shape Model (MASM) whereas the active contour model is based on the Chan-Vese functional. Our SC-FAC energy functional is able to overcome the drawback of noise while minimizing the fitting forces under the shape constraints. We conducted ...
“neurons”35. In this work, using the morphological parameters of a defect as the input layer, the ANN model would assign its confidences (percent probability) in the defect being a GEP, LoF, or KH in the output layer. The defect would be assigned to the type with the highest ...
In this paper, we propose a framework for link prediction in bipartite networks by combining the similarity based structure and the latent feature model from a new perspective. The framework is called Similarity Regularized Nonnegative Matrix Factorization (SRNMF), which explicitly takes the local ...