Harnessing the Experience Web to Support User-Generated Product Reviews. - Ruihai Dong; Markus Schaal; Michael P. O'Mahony; Kevin McCarthy; Barry Smyth (ICCBR, 2012)

Towards an intelligent reviewer's assistant: recommending topics to help users to write better product reviews. - Ruihai Dong; Kevin McCarthy; Michael P. O'Mahony; Markus Schaal; Barry Smyth (IUI, 2012)

First demonstration of the intelligent reviewer's assistant. - Ruihai Dong; Kevin McCarthy; Michael P. O'Mahony; Markus Schaal; Barry Smyth (IUI, 2012)

The demonstration of the reviewer's assistant. - Ruihai Dong; Markus Schaal; Michael P. O'Mahony; Kevin McCarthy; Barry Smyth (RecSys, 2012)

Unsupervised Topic Extraction for the Reviewer's Assistant. - Ruihai Dong; Markus Schaal; Michael P. O'Mahony; Kevin McCarthy; Barry Smyth (SGAI Conf., 2012)

Opinionated Product Recommendation. - Ruihai Dong; Markus Schaal; Michael P. O'Mahony; Kevin McCarthy; Barry Smyth (ICCBR, 2013)

Mining Features and Sentiment from Review Experiences. - Ruihai Dong; Markus Schaal; Michael P. O'Mahony; Kevin McCarthy; Barry Smyth (ICCBR, 2013)

Topic Extraction from Online Reviews for Classification and Recommendation. - Ruihai Dong; Markus Schaal; Michael P. O'Mahony; Barry Smyth (IJCAI, 2013)

Sentimental product recommendation. - Ruihai Dong; Michael P. O'Mahony; Markus Schaal; Kevin McCarthy; Barry Smyth (RecSys, 2013)

Further Experiments in Opinionated Product Recommendation. - Ruihai Dong; Michael P. O'Mahony; Barry Smyth (ICCBR, 2014)

Case-Studies in Mining User-Generated Reviews for Recommendation. - Ruihai Dong; Michael P. O'Mahony; Kevin McCarthy; Barry Smyth (Advances in Social Media Analysis, 2015)

Personalized Opinion-Based Recommendation. - Ruihai Dong; Barry Smyth (ICCBR, 2016)

Context-Aware Sentiment Detection from Ratings. - Yichao Lu; Ruihai Dong; Barry Smyth (SGAI Conf., 2016)

From More-Like-This to Better-Than-This: Hotel Recommendations from User Generated Reviews. - Ruihai Dong; Barry Smyth (UMAP, 2016)

Combining similarity and sentiment in opinion mining for product recommendation. - Ruihai Dong; Michael P. O'Mahony; Markus Schaal; Kevin McCarthy; Barry Smyth (J. Intell. Inf. Syst., 2016)

Multi-level Attention-Based Neural Networks for Distant Supervised Relation Extraction. - Linyi Yang; Tin Lok James Ng; Catherine Mooney; Ruihai Dong (AICS, 2017)

User-Based Opinion-based Recommendation. - Ruihai Dong; Barry Smyth (IJCAI, 2017)

Intelligent Auto-grading System. - Zining Wang; Jianli Liu; Ruihai Dong (CCIS, 2018)

Explainable Text-Driven Neural Network for Stock Prediction. - Linyi Yang; Zheng Zhang 042; Su Xiong; Lirui Wei; James Ng; Lina Xu; Ruihai Dong (CCIS, 2018)

Convolutional Matrix Factorization for Recommendation Explanation. - Yichao Lu; Ruihai Dong; Barry Smyth (IUI Companion, 2018)

Why I like it: multi-task learning for recommendation and explanation. - Yichao Lu; Ruihai Dong; Barry Smyth (RecSys, 2018)

Coevolutionary Recommendation Model: Mutual Learning between Ratings and Reviews. - Yichao Lu; Ruihai Dong; Barry Smyth (WWW, 2018)

Context-Aware Co-attention Neural Network for Service Recommendations. - Lei Li 042; Ruihai Dong; Li Chen 009 (ICDE Workshops, 2019)

MAEC: A Multimodal Aligned Earnings Conference Call Dataset for Financial Risk Prediction. - Jiazheng Li 002; Linyi Yang; Barry Smyth; Ruihai Dong (CIKM, 2020)

Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification. - Linyi Yang; Eoin M. Kenny; Tin Lok James Ng; Yi Yang 042; Barry Smyth; Ruihai Dong (COLING, 2020)

Overlap Training to Mitigate Inconsistencies Caused by Image Tiling in CNNs. - Yu An; Qing Ye; Jiulin Guo; Ruihai Dong (SGAI Conf., 2020)

HTML: Hierarchical Transformer-based Multi-task Learning for Volatility Prediction. - Linyi Yang; Tin Lok James Ng; Barry Smyth; Ruihai Dong (WWW, 2020)

Visual Recognition of traffic police gestures with convolutional pose machine and handcrafted features. - Jian He; Cheng Zhang 033; Xinlin He; Ruihai Dong (Neurocomputing, 2020)

An Energy-Efficient Fall Detection Method Based on FD-DNN for Elderly People. - Leyuan Liu 003; Yibin Hou; Jian He; Jonathan Lungu; Ruihai Dong (Sensors, 2020)

Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis. - Linyi Yang; Jiazheng Li 002; Padraig Cunningham; Yue Zhang 004; Barry Smyth; Ruihai Dong (ACL/IJCNLP (1), 2021)

Bias Bubbles: Using Semi-Supervised Learning to Measure How Many Biased News Articles Are Around Us. - Qin Ruan; Brian Mac Namee; Ruihai Dong (AICS, 2021)

Emotion Class-Wise Aware Loss for Image Emotion Classification. - Sinuo Deng; Lifang Wu; Ge Shi 002; Heng Zhang; Wenjin Hu 002; Ruihai Dong (CICAI, 2021)

Measuring Financial Time Series Similarity with a View to Identifying Profitable Stock Market Opportunities. - Rian Dolphin; Barry Smyth; Yang Xu; Ruihai Dong (ICCBR, 2021)

Deciphering Ancient Chinese Oracle Bone Inscriptions Using Case-Based Reasoning. - Gechuan Zhang; Dairui Liu; Barry Smyth; Ruihai Dong (ICCBR, 2021)

Conversation and Recommendation: Knowledge-Enhanced Personalized Dialog System. - Ming He 001; Tong Shen; Ruihai Dong (ICWE, 2021)

DARES: An Asynchronous Distributed Recommender System Using Deep Reinforcement Learning. - Bichen Shi; Elias Z. Tragos; Makbule Gulcin Ozsoy; Ruihai Dong; Neil Hurley; Barry Smyth; Aonghus Lawlor (IEEE Access, 2021)

Heterogeneous Graph Neural Networks for Multi-label Text Classification. - Irene Li; Tianxiao Li; Yixin Li; Ruihai Dong; Toyotaro Suzumura (CoRR, 2021)

Fact Check: Analyzing Financial Events from Multilingual News Sources. - Linyi Yang; Tin Lok James Ng; Barry Smyth; Ruihai Dong (CoRR, 2021)

Pseudo-labelling Enhanced Media Bias Detection. - Qin Ruan; Brian Mac Namee; Ruihai Dong (CoRR, 2021)

An Information Gain-Based Model and an Attention-Based RNN for Wearable Human Activity Recognition. - Leyuan Liu 003; Jian He; Keyan Ren; Jonathan Lungu; Yibin Hou; Ruihai Dong (Entropy, 2021)

Deep convolutional neural network for automatic fault recognition from 3D seismic datasets. - Yu An; Jiulin Guo; Qing Ye; Conrad Childs; John Walsh; Ruihai Dong (Comput. Geosci., 2021)

CAESAR: context-aware explanation based on supervised attention for service recommendations. - Lei Li 042; Li Chen 009; Ruihai Dong (J. Intell. Inf. Syst., 2021)

NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-Task Financial Forecasting. - Linyi Yang; Jiazheng Li 002; Ruihai Dong; Yue Zhang 004; Barry Smyth (AAAI, 2022)

A Novel Perspective to Look At Attention: Bi-level Attention-based Explainable Topic Modeling for News Classification. - Dairui Liu; Derek Greene; Ruihai Dong (ACL (Findings), 2022)

A Machine Learning Approach to Industry Classification in Financial Markets. - Rian Dolphin; Barry Smyth; Ruihai Dong (AICS, 2022)

MARF: User-Item Mutual Aware Representation with Feedback. - Qinqin Wang; Khalil Muhammad; Diarmuid O'Reilly-Morgan; Barry Smyth; Elias Z. Tragos; Aonghus Lawlor; Neil Hurley; Ruihai Dong (ICWE, 2022)

Entity-Enhanced Graph Convolutional Network for Accurate and Explainable Recommendation. - Qinqin Wang; Elias Z. Tragos; Neil Hurley; Barry Smyth; Aonghus Lawlor; Ruihai Dong (UMAP, 2022)

Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems. - Qinqin Wang; Diarmuid O'Reilly-Morgan; Elias Z. Tragos; Neil Hurley; Barry Smyth; Aonghus Lawlor; Ruihai Dong (IEEE Access, 2022)

Stock Embeddings: Learning Distributed Representations for Financial Assets. - Rian Dolphin; Barry Smyth; Ruihai Dong (CoRR, 2022)

Disentangling Noise Patterns From Seismic Images: Noise Reduction and Style Transfer. - Haiwen Du; Yu An; Qing Ye; Jiulin Guo; Lu Liu; Dongjie Zhu; Conrad Childs; John Walsh; Ruihai Dong (IEEE Trans. Geosci. Remote. Sens., 2022)

Learning to Generalize for Cross-domain QA. - Yingjie Niu; Linyi Yang; Ruihai Dong; Yue Zhang 004 (ACL (Findings), 2023)

Reducing Media Bias in News Headlines. - Qin Ruan; Brian Mac Namee; Ruihai Dong (AICS, 2023)

A Flash Attention Transformer for Multi-Behaviour Recommendation. - Tendai Mukande; Esraa Ali; Annalina Caputo; Ruihai Dong; Noel E. O'Connor (CIKM, 2023)

A Case-Based Reasoning Approach to Company Sector Classification Using a Novel Time-Series Case Representation. - Rian Dolphin; Barry Smyth; Ruihai Dong (ICCBR, 2023)

A Sparse Sinkhorn Transformer for Multi-Behaviour Recommendation. - Tendai Mukande; Esraa Ali; Annalina Caputo; Ruihai Dong; Noel E. O'Connor (ICEBE, 2023)

Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases. - Haiwen Du; Zheng Ju; Yu An; Honghui Du; Dongjie Zhu; Zhaoshuo Tian; Aonghus Lawlor; Ruihai Dong (ICONIP (15), 2023)

Adaptive Adversarial Samples Based Active Learning for Medical Image Classification. - Siteng Ma; Yu An; Jing Wang; Aonghus Lawlor; Ruihai Dong (ICPRAM, 2023)

✨ Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations. - Boming Yang; Dairui Liu; Toyotaro Suzumura; Ruihai Dong; Irene Li (RecSys, 2023)

Unveiling the Relationship Between News Recommendation Algorithms and Media Bias: A Simulation-Based Analysis of the Evolution of Bias Prevalence. - Qin Ruan; Brian Mac Namee; Ruihai Dong (SGAI Conf., 2023)

The Influence of Media Bias on News Recommender Systems. - Qin Ruan; Brian Mac Namee; Ruihai Dong (UMAP, 2023)

Understanding the Effect of Different Prior Knowledge on CNN Fault Interpreter. - Yu An; Ruihai Dong (IEEE Access, 2023)

Industry Classification Using a Novel Financial Time-Series Case Representation. - Rian Dolphin; Barry Smyth; Ruihai Dong (CoRR, 2023)

Enhancing Topic Extraction in Recommender Systems with Entropy Regularization. - Xuefei Jiang; Dairui Liu; Ruihai Dong (CoRR, 2023)

Topic-Centric Explanations for News Recommendation. - Dairui Liu; Derek Greene; Irene Li; Ruihai Dong (CoRR, 2023)

Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations. - Boming Yang; Dairui Liu; Toyotaro Suzumura; Ruihai Dong; Irene Li (CoRR, 2023)

RecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language Models. - Dairui Liu; Boming Yang; Honghui Du; Derek Greene; Aonghus Lawlor; Ruihai Dong; Irene Li (CoRR, 2023)

Human activity recognition based on multi-modal fusion. - Cheng Zhang 033; Tianqi Zu; Yibin Hou; Jian He; Shengqi Yang; Ruihai Dong (CCF Trans. Pervasive Comput. Interact., 2023)

NLP-Based Analysis of Annual Reports: Asset Volatility Prediction and Portfolio Strategy Application. - Xiao Li; Yang Xu; Linyi Yang; Yue Zhang 004; Ruihai Dong (AICS, 2024)

Vulnerable by Design: Reconsidering User Vulnerability and Recommender Systems. - Megan Nyhan; Josephine Griffith; Qin Ruan; Tai Tan Mai; Ruihai Dong; Susan Leavy (BIR/IR4U2, 2024)

RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models. - Dairui Liu; Boming Yang; Honghui Du; Derek Greene; Neil Hurley; Aonghus Lawlor; Ruihai Dong; Irene Li (CIKM, 2024)

MMCRec: Towards Multi-modal Generative AI in Conversational Recommendation. - Tendai Mukande; Esraa Ali; Annalina Caputo; Ruihai Dong; Noel E. O'Connor (ECIR (3), 2024)

Contrastive Learning of Asset Embeddings from Financial Time Series. - Rian Dolphin; Barry Smyth; Ruihai Dong (ICAIF, 2024)

Evaluating Financial Relational Graphs: Interpretation Before Prediction. - Yingjie Niu; Lanxin Lu; Rian Dolphin; Valerio Potì; Ruihai Dong (ICAIF, 2024)

Breaking the Barrier: Selective Uncertainty-Based Active Learning for Medical Image Segmentation. - Siteng Ma; Haochang Wu; Aonghus Lawlor; Ruihai Dong (ICASSP, 2024)

Adaptive Curriculum Query Strategy for Active Learning in Medical Image Classification. - Siteng Ma; Honghui Du; Kathleen M. Curran; Aonghus Lawlor; Ruihai Dong (MICCAI (11), 2024)

EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models. - Irene Li; Ruihai Dong; Lei Li 042; Li Chen 009 (RecSys, 2024)

Rewriting Bias: Mitigating Media Bias in News Recommender Systems through Automated Rewriting. - Qin Ruan; Jin Xu; Susan Leavy; Brian Mac Namee; Ruihai Dong (UMAP, 2024)

The Effects of Media Bias on News Recommendations. - Qin Ruan; Brian Mac Namee; Ruihai Dong (IEEE Access, 2024)

A Comparative Study of Vision Transformer and Convolutional Neural Network Models in Geological Fault Detection. - Jing Wang 176; Siteng Ma; Yu An; Ruihai Dong (IEEE Access, 2024)

Model-data-driven adversarial active learning for brain tumor segmentation. - Siteng Ma; Prateek Mathur; Zheng Ju; Aonghus Lawlor; Ruihai Dong (Comput. Biol. Medicine, 2024)

ARTAI: An Evaluation Platform to Assess Societal Risk of Recommender Algorithms. - Qin Ruan; Jin Xu; Ruihai Dong; Arjumand Younus; Tai Tan Mai; Barry O'Sullivan; Susan Leavy (CoRR, 2024)

Transformers4NewsRec: A Transformer-based News Recommendation Framework. - Dairui Liu; Honghui Du; Boming Yang; Neil Hurley; Aonghus Lawlor; Irene Li; Derek Greene; Ruihai Dong (CoRR, 2024)

Rewritten Media Bias News Headlines. - Qin Ruan; Jin Xu; Susan Leavy; Brian Mac Namee; Ruihai Dong (Zenodo, 2024)

Learning to compose diversified prompts for image emotion classification. - Sinuo Deng; Lifang Wu; Ge Shi 002; Lehao Xing; Meng Jian; Ye Xiang; Ruihai Dong (Comput. Vis. Media, 2024)

Algorithmic Transparency: The EU Digital Services Act and Young People's Experiences of Online Platforms. - Megan Nyhan; Susan Leavy; Pranav Narula; Kevin Doherty; Barry O'Sullivan; Ruihai Dong; Izzy Fox; Josephine Griffith (EWAF, 2025)

Towards Efficient Hypergraph Representation Learning for Multi-Behaviour Recommender Systems. - Tendai Mukande; Esraa Ali; Annalina Caputo; Ruihai Dong; Noel E. O'Connor (WWW (Companion Volume), 2025)

Deep Learning Approaches for Medical Imaging Under Varying Degrees of Label Availability: A Comprehensive Survey. - Siteng Ma; Honghui Du; Yu An; Jing Wang; Qinqin Wang; Haochang Wu; Aonghus Lawlor; Ruihai Dong (CoRR, 2025)

Topic-Centric Explanations for News Recommendation. - Dairui Liu; Derek Greene; Irene Li; Xuefei Jiang; Ruihai Dong (Trans. Recomm. Syst., 2025)

NGAT: A Node-level Graph Attention Network for Long-term Stock Prediction. - Yingjie Niu; Mingchuan Zhao; Valerio Potì; Ruihai Dong (CoRR, 2025)