Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Shajalal, Md."'
Customers' reviews and feedback play crucial role on electronic commerce~(E-commerce) platforms like Amazon, Zalando, and eBay in influencing other customers' purchasing decisions. However, there is a prevailing concern that sellers often post fake o
Externí odkaz:
http://arxiv.org/abs/2407.21056
Publikováno v:
Explainable Artificial Intelligence. xAI 2024. Communications in Computer and Information Science, vol 2156. Springer, Cham
Smart home systems are gaining popularity as homeowners strive to enhance their living and working environments while minimizing energy consumption. However, the adoption of artificial intelligence (AI)-enabled decision-making models in smart home sy
Externí odkaz:
http://arxiv.org/abs/2404.16074
Autor:
Kern, Dean-Robin, Stevens, Gunnar, Dethier, Erik, Naveed, Sidra, Alizadeh, Fatemeh, Du, Delong, Shajalal, Md
Explainable Artificial Intelligence is a concept aimed at making complex algorithms transparent to users through a uniform solution. Researchers have highlighted the importance of integrating domain specific contexts to develop explanations tailored
Externí odkaz:
http://arxiv.org/abs/2311.11655
Publikováno v:
Explainable Artificial Intelligence. xAI 2023. Communications in Computer and Information Science, vol 1902. Springer, Cham
Recent technological advancements have led to a large number of patents in a diverse range of domains, making it challenging for human experts to analyze and manage. State-of-the-art methods for multi-label patent classification rely on deep neural n
Externí odkaz:
http://arxiv.org/abs/2310.20478
Autor:
Karim, Md. Rezaul, Comet, Lina Molinas, Shajalal, Md, Beyan, Oya Deniz, Rebholz-Schuhmann, Dietrich, Decker, Stefan
Domain experts often rely on most recent knowledge for apprehending and disseminating specific biological processes that help them design strategies for developing prevention and therapeutic decision-making in various disease scenarios. A challenging
Externí odkaz:
http://arxiv.org/abs/2310.08365
Publikováno v:
NLPIR 2023: 2023 7th International Conference on Natural Language Processing and Information Retrieval, Seoul, Republic of Korea, December 2023
Sentiment Analysis (SA) is an indispensable task for many real-world applications. Compared to limited resourced languages (i.e., Arabic, Bengali), most of the research on SA are conducted for high resourced languages (i.e., English, Chinese). Moreov
Externí odkaz:
http://arxiv.org/abs/2309.13731
Publikováno v:
Speech and Language Technologies for Low-Resource Languages . SPELLL 2022. Communications in Computer and Information Science, vol 1802. Springer, Cham
Textual entailment recognition is one of the basic natural language understanding(NLU) tasks. Understanding the meaning of sentences is a prerequisite before applying any natural language processing(NLP) techniques to automatically recognize the text
Externí odkaz:
http://arxiv.org/abs/2210.09723
Autor:
Karim, Md. Rezaul, Shajalal, Md., Graß, Alex, Döhmen, Till, Chala, Sisay Adugna, Boden, Alexander, Beecks, Christian, Decker, Stefan
Publikováno v:
2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)
Deep neural networks (DNNs) have been shown to outperform traditional machine learning algorithms in a broad variety of application domains due to their effectiveness in modeling complex problems and handling high-dimensional datasets. Many real-life
Externí odkaz:
http://arxiv.org/abs/2208.13405
Autor:
Karim, Md. Rezaul, Dey, Sumon Kanti, Islam, Tanhim, Shajalal, Md., Chakravarthi, Bharathi Raja
Publikováno v:
Pre-print for our paper at International Conference on Speech & Language Technology for Low-resource Languages (SPELLL'2022)
Numerous machine learning (ML) and deep learning (DL)-based approaches have been proposed to utilize textual data from social media for anti-social behavior analysis like cyberbullying, fake news detection, and identification of hate speech mainly fo
Externí odkaz:
http://arxiv.org/abs/2204.10196
Publikováno v:
In Technological Forecasting & Social Change September 2024 206
