Outputs (1140)

A practical exploration of the convergence of case-based reasoning and explainable artificial intelligence. (2024)
Journal Article
PRADEEP, P., CARO-MARTÍNEZ, M. and WIJEKOON, A. [2024]. A practical exploration of the convergence of case-based reasoning and explainable artificial intelligence. Expert systems with applications [online], In Press, article number 124733. Available from: https://doi.org/10.1016/j.eswa.2024.124733

As Artificial Intelligence (AI) systems become increasingly complex, ensuring their decisions are transparent and understandable to users has become paramount. This paper explores the integration of Case-Based Reasoning (CBR) with E... Read More about A practical exploration of the convergence of case-based reasoning and explainable artificial intelligence..

Towards the automation of systematic reviews using natural language processing, machine learning, and deep learning: a comprehensive review. (2024)
Journal Article
OFORI-BOATENG, R., ACEVES-MARTINS, M., WIRATUNGA, N. and MORENO-GARCIA, C.F. 2024. Towards the automation of systematic reviews using natural language processing, machine learning, and deep learning: a comprehensive review. Artificial intelligence review [online], 57(8), article number 200. Available from: https://doi.org/10.1007/s10462-024-10844-w

Systematic reviews (SRs) constitute a critical foundation for evidence-based decision-making and policy formulation across various disciplines, particularly in healthcare and beyond. However, the inherently rigorous and structured nature of the SR pr... Read More about Towards the automation of systematic reviews using natural language processing, machine learning, and deep learning: a comprehensive review..

Curriculum analysis for data systems education. (2024)
Conference Proceeding
MIEDEMA, D., TAIPALUS, T., AJANOVSKI, V.V., ALAWINI, A., GOODFELLOW, M., LIUT, M., PELTSVERGER, S. and YOUNG, T. 2024. Curriculum analysis for data systems education. In Monga, M., Lonati, V. Barendsen, E. et al. (eds.) ITiCSE 2024: innovation and technology in computer science education: proceedings of the 29th Innovation and technology in computer science education 2024, 8-10 July 2024, Milan, Italy. New York: ACM [online], volume 2, pages 761-762. Available from: https://doi.org/10.1145/3649405.3659529

The field of data systems has seen quick advances due to the popularization of data science, machine learning, and real-time analytics. In industry contexts, system features such as recommendation systems, chatbots and reverse image search require ef... Read More about Curriculum analysis for data systems education..

A plan for a joint study into the impacts of AI on professional competencies of IT professionals and implications for computing students. (2024)
Conference Proceeding
CLEAR, T., CAJANDER, A., CLEAR, A., MCDERMOTT, R., BERGQVIST, A., DANIELS, M., DIVITINI, M., FORSHAW, M., HUMBLE, N., KASINIDOU, M., KLEANTHOUS, S., KULTUR, C., PARVINI, G., POLASH, M. and ZHU, T. 2024. A plan for a joint study into the impacts of AI on professional competencies of IT professionals and implications for computing students. In Monga, M., Lonati, V. Barendsen, E. et al. (eds.) ITiCSE 2024: innovation and technology in computer science education: proceedings of the 29th Innovation and technology in computer science education 2024 (ITiCSE 2024), 8-10 July 2024, Milan, Italy. New York: ACM [online], volume 2, pages 757-758. Available from: https://doi.org/10.1145/3649405.3659527

As Artificial Intelligence (AI) continues to make its presence felt in transforming workplaces around the world, and the Information Technology industry in particular, it is essential to understand its impact on the work practices of IT professionals... Read More about A plan for a joint study into the impacts of AI on professional competencies of IT professionals and implications for computing students..

A zero-shot monolingual dual stage information retrieval system for Spanish biomedical systematic literature reviews. (2024)
Conference Proceeding
OFORI-BOATENG, R., ACEVES-MARTINS, M., WIRATUNGA, N. and MORENO-GARCIA, C. 2024. A zero-shot monolingual dual stage information retrieval system for Spanish biomedical systematic literature reviews. In Duh, K., Gomez, H. and Bethard, S. (eds.) Proceedings of the 2024 North American Chapter of the Association for Computational Linguistics conference (NAACL 2024): human language technologies, 16-21 June 2024, Mexico City, Mexico. Stroudsburg, PA: ACL [online], volume 1: long papers, pages 3725-3736. Available from: https://aclanthology.org/2024.naacl-long.206

Systematic Reviews (SRs) are foundational in healthcare for synthesising evidence to inform clinical practices. Traditionally skewed towards English-language databases, SRs often exclude significant research in other languages, leading to potential b... Read More about A zero-shot monolingual dual stage information retrieval system for Spanish biomedical systematic literature reviews..

SSA-LHCD: a singular spectrum analysis-driven lightweight network with 2-D self-attention for hyperspectral change detection. (2024)
Journal Article
LI, Y., REN, J., YAN, Y., SUN, G. and MA, P. 2024. SSA-LHCD: a singular spectrum analysis-driven lightweight network with 2-D self-attention for hyperspectral change detection. Remote sensing [online], 16(3), article number 2353. Available from: https://doi.org/10.3390/rs16132353

As an emerging research hotspot in contemporary remote sensing, hyperspectral change detection (HCD) has attracted increasing attention in remote sensing Earth observation, covering land mapping changes and anomaly detection. This is primarily attrib... Read More about SSA-LHCD: a singular spectrum analysis-driven lightweight network with 2-D self-attention for hyperspectral change detection..

A multimodel-based screening framework for C-19 using deep learning-inspired data fusion. (2024)
Journal Article
SHANKAR, A., RIZWAN, P., MEKALA, M.S., ELYAN, E., GANDOMI, A.H., MAPLE, C. and RODRIGUES, J.J.P.C. 2024. A multimodel-based screening framework for C-19 using deep learning-inspired data fusion. IEEE journal of biomedical and health informatics [online], Early Access. Available from: https://doi.org/10.1109/JBHI.2024.3400878

In recent times, there has been a notable rise in the utilization of Internet of Medical Things (IoMT) frameworks particularly those based on edge computing, to enhance remote monitoring in healthcare applications. Most existing models in this field... Read More about A multimodel-based screening framework for C-19 using deep learning-inspired data fusion..

CBR-RAG: case-based reasoning for retrieval augmented generation in LLMs for legal question answering. (2024)
Conference Proceeding
WIRATUNGA, N., ABEYRATNE, R., JAYAWARDENA, L., MARTIN, K., MASSIE, S., NKISI-ORJI, I., WEERASINGHE, R., LIRET, A. and FLEISCH, B. 2024. CBR-RAG: case-based reasoning for retrieval augmented generation in LLMs for legal question answering. In Recio-Garcia, J.A., Orozco-del-Castillo, M.G. and Bridge, D (eds.) Case-based reasoning research and development: proceedings of the 32nd International conference of case-based reasoning research and development 2024 (ICCBR 2024), 1-4 July 2024, Merida, Mexico. Lecture notes in computer science, 14775. Cham: Springer [online], pages 445-460. Available from: https://doi.org/10.1007/978-3-031-63646-2_29

Retrieval-Augmented Generation (RAG) enhances Large Language Model (LLM) output by providing prior knowledge as context to input. This is beneficial for knowledge-intensive and expert reliant tasks, including legal question-answering, which require e... Read More about CBR-RAG: case-based reasoning for retrieval augmented generation in LLMs for legal question answering..

HEADS: hybrid ensemble anomaly detection system for Internet-of-Things networks. (2024)
Conference Proceeding
AHMAD, Z., PETROVSKI, A., ARIFEEN, M., KHAN, A.S. and SHAH, S.A. 2024. HEADS: hybrid ensemble anomaly detection system for Internet-of-Things networks. In Iliadis, L., Maglogiannis, I., Papaleonidas, A., Pimenidis, E. and Jayne, C. (eds.) Engineering applications on neural networks: proceedings of the 25th International Engineering applications on neural networks 2024 (EANN 2024), 27-30 June 2024, Corfu, Greece. Communications in computer and information science, 2141. Cham: Springer [online], pages 178-190. Available from: https://doi.org/10.1007/978-3-031-62495-7_14

The rapid expansion of Internet-of-Things (IoT) devices has revolutionized connectivity, facilitating the exchange of extensive data within IoT networks via the traditional internet. However, this innovation has also increased security concerns due t... Read More about HEADS: hybrid ensemble anomaly detection system for Internet-of-Things networks..

Prompting-to-distill semantic knowledge for few-shot learning. (2024)
Journal Article
JI, H., GAO, Z., REN, J., WANG, X.-A., GAO, T., SUN, W. and MA, P. 2024. Prompting-to-distill semantic knowledge for few-shot learning. IEEE geoscience and remote sensing letters [online], 21, article 6011605. Available from: https://doi.org/10.1109/lgrs.2024.3414505

Recognizing visual patterns in low-data regime necessitates deep neural networks to glean generalized representations from limited training samples. In this paper, we propose a novel few-shot classification method, namely ProDFSL, leveraging multi-mo... Read More about Prompting-to-distill semantic knowledge for few-shot learning..