Results 21 to 30 of about 76,023 (254)

Context-Aware Negative Sampling for Sequential Recommendation

IEEE Access
Recommender systems have become essential in large-scale e-commerce and content platforms. While user preferences are crucial in generating recommendations, the context in which recommendations are made—such as time, location, and occasion— ...
Jinseok Seol, Jaesik Choi
doaj   +1 more source

Towards Interpretable Deep Learning Models for Knowledge Tracing

, 2020
As an important technique for modeling the knowledge states of learners, the traditional knowledge tracing (KT) models have been widely used to support intelligent tutoring systems and MOOC platforms.
F Arbabzadah, H Yang, L Arras, M Feng, M Grégoire, M Schuster, RSJ Baker, S Bach, S Hochreiter   +8 more
core   +1 more source

Instantiating the onEEGwaveLAD Framework for Real-Time Muscle Artefact Identification and Mitigation in EEG Signals

Sensors
While electroencephalography is extremely useful for studying brain activity, EEG data is always contaminated by a wide range of artefacts. Many techniques exist to identify and remove such artefacts, primarily offline, with and without human supervision
Luca Longo, Richard Reilly
doaj   +1 more source

Carbon price interval prediction by bidirectional long short-term memory and multi-objective optimization with an asymmetric scaling approach

Energy Reports
Accurate carbon price prediction is essential for decision-making and risk management. Most existing predictive models produce deterministic results and fail to account for uncertainties in carbon prices. To address this limitation, this study introduces
Di Sha, Arne Johannssen, Xianyi Zeng, Zhenglei He, Hanhan Wu, Kim Phuc Tran   +5 more
doaj   +1 more source

A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners

IEEE Access
Due to market deregulation and globalisation, competitive environments in various sectors continuously evolve, leading to increased customer churn. Effectively anticipating and mitigating customer churn is vital for businesses to retain their customer ...
Awais Manzoor, M. Atif Qureshi, Etain Kidney, Luca Longo   +3 more
doaj   +1 more source

Artificial Intelligence Explained for Nonexperts

Seminars in Musculoskeletal Radiology, 2020
AbstractArtificial intelligence (AI) has made stunning progress in the last decade, made possible largely due to the advances in training deep neural networks with large data sets. Many of these solutions, initially developed for natural images, speech, or text, are now becoming successful in medical imaging.
Narges, Razavian, Florian, Knoll, Krzysztof J, Geras   +2 more
openaire   +3 more sources

Advancing Deliberative Discourse Measurement: The Intersection with Computational Abstract Argumentation in Discourse Quality Evaluations

Systems
This research investigates the potential of computational argumentation, specifically the application of the Abstract Argumentation Framework (AAF), to enhance the evaluation of deliberative quality in public discourse.
Sanjay Kumar, Jane Suiter, Luca Longo
doaj   +1 more source

Perspectives in educating molecular pathologists on liquid biopsy: Toward integrative, equitable, and decentralized precision oncology

Molecular Oncology, EarlyView.
Liquid biopsy enables minimally invasive, real‐time molecular profiling through analysis of circulating biomarkers in biological fluids. This Perspective highlights the importance of training pathologists through integrative educational programs, such as the European Masters in Molecular Pathology, to ensure effective and equitable implementation of ...
Marius Ilié, Umberto Malapelle, Catherine Alix‐Panabières, Claus Lindbjerg Andersen, Sandra Chlebowski, Vivien Lake, Caroline Lacoux, Virginie Lespinet‐Fabre, Olivier Bordone, Simon Heeke, Christophe Bontoux, Ellen Heitzer, Klaus Pantel, Paul Hofman   +13 more
wiley   +1 more source

Exploring the clinical value of concept-based AI explanations in gastrointestinal disease detection

Scientific Reports
Complex artificial intelligence models, like deep neural networks, have shown exceptional capabilities to detect early-stage polyps and tumors in the gastrointestinal tract.
Andrea M. Storås, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin, Wojciech Samek, Pål Halvorsen, Thomas de Lange, Yuichi Mori, Alexander Hann, Tyler M. Berzin, Sravanthi Parasa, Michael A. Riegler   +11 more
doaj   +1 more source

Visualizations for an Explainable Planning Agent

, 2018
In this paper, we report on the visualization capabilities of an Explainable AI Planning (XAIP) agent that can support human in the loop decision making.
Bellamy, Rachel K. E., Chakraborti, Tathagata, Dholakia, Mishal, Fadnis, Kshitij P., Kephart, Jeffrey O., Srivastava, Biplav, Talamadupula, Kartik   +6 more
core   +1 more source