no code implementations • 24 Jul 2024 • Md Shajalal, Md Atabuzzaman, Alexander Boden, Gunnar Stevens, Delong Du
Furthermore, the empirical user evaluation of the generated explanations concludes which important information needs to be considered in generating explanations in the context of fake review identification.
no code implementations • 23 Apr 2024 • Md Shajalal, Alexander Boden, Gunnar Stevens, Delong Du, Dean-Robin Kern
Smart home systems are gaining popularity as homeowners strive to enhance their living and working environments while minimizing energy consumption.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+1
no code implementations • 31 Oct 2023 • Md Shajalal, Sebastian Denef, Md. Rezaul Karim, Alexander Boden, Gunnar Stevens
Considering the relevance score, we then generate explanations by visualizing relevant words for the predicted patent class.
no code implementations • 24 Sep 2023 • Md. Atabuzzaman, Md Shajalal, Maksuda Bilkis Baby, Alexander Boden
This paper proposes an explainable sentiment classification framework for the Arabic language by introducing a noise layer on Bi-Directional Long Short-Term Memory (BiLSTM) and Convolutional Neural Networks (CNN)-BiLSTM models that overcome over-fitting problem.
no code implementations • 18 Oct 2022 • Md Shajalal, Md Atabuzzaman, Maksuda Bilkis Baby, Md Rezaul Karim, Alexander Boden
In this paper, we propose a novel approach to identifying the textual entailment relationship between text and hypothesis, thereby introducing a new semantic feature focusing on empirical threshold-based semantic text representation.
Natural Language Inference
Natural Language Understanding
+2
no code implementations • 29 Aug 2022 • Md. Rezaul Karim, Md. Shajalal, Alex Graß, Till Döhmen, Sisay Adugna Chala, Alexander Boden, Christian Beecks, Stefan Decker
Many real-life datasets, however, are of increasingly high dimensionality, where a large number of features may be irrelevant for both supervised and unsupervised learning tasks.