Research

Publications

• Weipeng Huang, Junjie Tao, Changbo Deng, Ming Fan, Wenqiang Wan, Qi Xiong, Guangyuan Piao, Renyi Divergence Deep Mutual Learning, 2022

• Guangyuan Piao, Fashion Recommendations with Operational-aware Neural Networks, Discovery Challenge at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)[A], 2021.

• Siddhesh Chaubal, Mateusz Rzepecki, Patrick K. Nicholson, Guangyuan Piao, Alessandra Sala, Geometric Heuristics for Transfer Learning with Decision Trees, International

• Conference on Information and Knowledge Management (CIKM, 21.7% acceptance rate)[A], 2021. [bibtex]

• Guangyuan Piao, Patrick K. Nicholson, Thomas Voith, Diego Lugones, Apparatus and a method for processing time series data, Patent, 2021.

• Guangyuan Piao, A Simple Language Independent Approach for Distinguishing Individuals onSocial Media, The 32nd ACM Conference on Hypertext and Social Media (Hypertext)[A], 2021. [bibtex] [code]

• Guangyuan Piao, Weipeng Huang, Learning to Predict the Departure Dynamics of Wikidata Editors, The 20th International Semantic Web Conference (ISWC, 18% acceptance rate)[A], 2021. [bibtex] [code]

• Gopika Premsankar, Guangyuan Piao, Patrick Nicholson, Mario Di Francesco, Diego Lugones, Data-driven Energy Conservation in Cellular Networks: A Systems Approach, IEEE Transactions on Network and Service Management (IF: 3.8), 2021. [bibtex]

• Guangyuan Piao, Recommending Knowledge Concepts on MOOC Platforms with Meta-path-based Representation Learning, The 14th Educational Data Mining Conference (EDM)[B], Paris, France, 06/2021. [bibtex] [code] [video]

• Shanti Chilukuri, Guangyuan Piao, Diego Lugones and Dirk Pesch, Deadline-Aware TDMA Scheduling for Multihop Networks Using Reinforcement Learning, The 20th IFIP Networking Conference (Networking, 25.9% acceptance rate)[A], Virtual, Finland, 06/2021. [bibtex]

• Weipeng Huang, Nishma Laitonjam, Guangyuan Piao, Neil Hurley, Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach, The 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2021, 20% acceptance rate)[A], Delhi, India, 05/2021. [bibtex]

• Guangyuan Piao, Scholarly Text Classification with Sentence BERT and Entity Embeddings, SDPRA Workshop at the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Delhi, India, 05/2021. [bibtex] [code]

• Weipeng Huang, Guangyuan Piao, Raul Moreno Salinas, Neil Hurley, Partially Observable Markov Decision Process Modelling for Assessing Hierarchies, The 12th Asian Conference on Machine Learning (ACML, 33% acceptance rate) [Best Student Paper Award], Bangkok, Thailand, 11/2020. [bibtex]

• Guangyuan Piao, Weipeng Huang, Regression-enhanced Random Forests with Personalized Patching for COVID-19 Retweet Prediction, CIKM AnalytiCup at International Conference on Knowledge and Management (CIKM), 10/2020. [bibtex] [code]

• Fattane Zarrinkalam, Stefano Faralli, Guangyuan Piao and Ebrahim Bagheri, Extracting, Mining and Predicting Users’ Interests from Social Media, (Foundationsand Trends@ in Information Retrieval, IF:3.5), 2020. [bibtex]

• Fattane Zarrinkalam, Stefano Faralli, Guangyuan Piao and Ebrahim Bagheri, Mining User Interests from Social Media, International Conference on Knowledge and Management (CIKM Tutorial) [A], 10/2020. [bibtex] [video]

• Fattane Zarrinkalam, Stefano Faralli, Guangyuan Piao and Ebrahim Bagheri, Mining User Interests from Social Media, International Joint Conference on Artificial Intelligence (IJCAI Tutorial) [A*], 07/2020. [bibtex] [video]

• Guangyuan Piao, Pat Nicholson, Diego Lugones, Env2Vec: Accelerating VNF Testing via Deep Learning, The 15th European Conference on Computer Systems (Eurosys, 18% acceptance rate)[A], Crete, Greece, 04/2020. [bibtex] [video] [ad video]

• Guangyuan Piao, Semantics-aware User Modeling and Recommender Systems in Online Social Networks, PhD Thesis, National University of Ireland Galway, 2018. [bibtex]

• Weipeng Huang, Guangyuan Piao, Raul Moreno Salinas, Neil Hurley, Evaluating Hierarchies through A Partially Observable Markov Decision Processes Methodology, arXiv:1908.07031, 2018.

• Weipeng Huang, Nishma Laitonjam, Guangyuan Piao, Neil Hurley, Bayesian Hierarchical Mixture Clustering using Multilevel Hierarchical Dirichlet Processes, arXiv:1905.05022, 2018.

• Guangyuan Piao and John G. Breslin, Domain-Aware Sentiment Classification with GRUs and CNNs, 1st place in the Semantic Sentiment Analysis challenge at the 15th Extended Semantic Web Conference (ESWC)[A], Crete, Greece, 06/2018. [bibtex]

• Guangyuan Piao and John G. Breslin, A Study of the Similarities of Entity Embeddings Learned from Different Aspects of a Knowledge Base for ItemRecommendations [Best Paper Award], The 1st Workshop on Deep Learning for Knowledge Graphs and Semantic Technologies at the 15th Extended Semantic Web Conference (ESWC)[A], Crete, Greece, 06/2018. [bibtex]

• Guangyuan Piao and John G. Breslin, Learning to Rank Tweets with Author-based Long Short-Term Memory Networks, The 18th International Conference on Web Engineering (ICWE)[B], Caceres, Spain, 06/2018. [bibtex]

• Guangyuan Piao and John G. Breslin, Transfer Learning via A Co-Factorization Model for Item Recommendations and Knowledge Graph Completionin Item Related Domains, The 15th Extended Semantic Web Conference (ESWC, 26% acceptance rate)[A], Crete, Greece, 06/2018. [bibtex] Check [code] by Yixin Cao@WWW'19

• Guangyuan Piao and John G. Breslin, Financial Aspect and Sentiment Predictions with Deep Neural Networks: An Ensemble Approach, Financial Opinion Mining and Question Answering Challenge at The Web Conference (WWW)[A*], Lyon, France, 04/2018. [bibtex]

• Guangyuan Piao and John G. Breslin, Inferring User Interests in Microblogging Social Networks: A Survey, UMUAI (IF: 3.4), 2018. [bibtex]

• Guangyuan Piao and John G. Breslin, Factorization Machines Leveraging Lightweight Linked Open Data-enabled Features for Top-N Recommendations , The 18th International Conference on Web Information Systems Engineering (WISE 2017, 25% acceptance rate)[A], Moscow, Russia, 07/10/2017. [bibtex]

• Guangyuan Piao and John G. Breslin, Leveraging Followee ListMemberships for Inferring User Interests for Passive Users on Twitter, The 28th ACM Conference on Hypertext and Social Media (Hypertext 2017, 27% acceptance rate)[A], Prague, Czech Republic, 04/07/2017. [bibtex] [ppt] [travel report]

• Guangyuan Piao and John G. Breslin, Inferring User Interests for Passive Users on Twitter by Leveraging Followee Biographies, The 39th European Conference on Information Retrieval (ECIR 2017, AR:26.7%)[A], Aberdeen, UK, 08/04/2017. [bibtex] [ppt]

• Guangyuan Piao and John G. Breslin, Interest Representation, Enrichment, Dynamics, and Propagation: A Study of the Synergetic Effect of Different User Modeling Dimensions for Personalized Recommendations on Twitter, The 20th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2016, AR:17.5% for long presentations)[B], Bologna, Italy, 19/11/2016. [bibtex] [ppt]

• Guangyuan Piao and John G. Breslin, User Modeling on Twitter with WordNet Synsets and DBpedia Concepts for Personalized Recommendations, The 25th ACM International Conference on Information and Knowledge Management (CIKM 2016, AR:23.5% for short)[A], Indianapolis, USA, 24/10/2016. [bibtex] [ppt]

• Guangyuan Piao and John G. Breslin, Exploring Dynamics and Semantics of User Interests for User Modeling on Twitter for Link Recommendations[Best Paper Award], The 12th International Conference on Semantic Systems (SEMANTiCS 2016, AR:21%), Leipzig, Germany, 12/09/2016. [bibtex] [ppt] [travel report]

• Guangyuan Piao and John G. Breslin, Towards Comprehensive User Modeling on the Social Web for Personalized Recommendations, The Doctoral Consortium at the 24th Conference on User Modeling, Adaptation and Personalization (UMAP 2016)[B], Halifax, Canada, 13/07/2016. Mentor: Tsvi Kuflik [bibtex]

• Guangyuan Piao and John G. Breslin, Analyzing MOOC Entries of Professionals on LinkedIn for User Modeling and Personalized MOOC Recommendations, The 24th Conference on User Modeling, Adaptation and Personalization (UMAP 2016)[B], Halifax, Canada, 13/07/2016. [bibtex]

• Guangyuan Piao and John G. Breslin, Analyzing Aggregated Semantics-enabled User Modeling on Google+ and Twitter for Personalized Link Recommendations, The 24th Conference on User Modeling, Adaptation and Personalization (UMAP 2016, AR:28% for short)[B], Halifax, Canada, 13/07/2016. [bibtex] [ppt] [travel report]

• Guangyuan Piao and John G. Breslin, Measuring Semantic Distance for Linked Open Data-enabled Recommender Systems , The 31st ACM/SIGAPP Symposium on Applied Computing (SAC 2016, AR:24%)[B], Pisa, Italy, 04/04/2016. [bibtex] [ppt] [travel report] [code]

• Guangyuan Piao and John G. Breslin, Computing the Semantic Similarity of Resources in DBpedia for Recommendation Purposes [Best Paper Candidate], The 5th Joint International Semantic Technology Conference (JIST 2015, AR:33%), Yichang, China, 12/11/2015. [bibtex] [ppt] [travel report]