Research

Publications

• Toward Exploring Knowledge Graphs with LLMs, 2024. [bibtex]

• Topologies of Reasoning: Demystifying Chains, Trees, and Graphs of Thoughts, 2024

• Renyi Divergence Deep Mutual Learning,
  Weipeng Huang, Junjie Tao, Changbo Deng, Ming Fan, Wenqiang Wan, Qi Xiong, Guangyuan Piao,
  ECML/PKDD [A], 24% acceptance rate, 2023

• Fashion Recommendations with Operational-aware Neural Networks,
  Guangyuan Piao,
  Discovery Challenge at ECML/PKDD [A], 2021.

• Geometric Heuristics for Transfer Learning with Decision Trees,
  Siddhesh Chaubal, Mateusz Rzepecki, Patrick K. Nicholson, Guangyuan Piao, Alessandra Sala,
  CIKM [A], 21.7% acceptance rate, 2021.
  [bibtex]

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

• A Simple Language Independent Approach for Distinguishing Individuals onSocial Media,
  Guangyuan Piao,
  Hypertext [A], 2021.
  [bibtex] [code]

• Learning to Predict the Departure Dynamics of Wikidata Editors,
  Guangyuan Piao, Weipeng Huang,
  ISWC [A], 18% acceptance rate, 2021.
  [bibtex] [code]

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

• Recommending Knowledge Concepts on MOOC Platforms with Meta-path-based Representation Learning,
  Guangyuan Piao,
  EDM [B], Paris, France, 06/2021.
  [bibtex] [code] [video]

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

• Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach,
  Weipeng Huang, Nishma Laitonjam, Guangyuan Piao, Neil Hurley,
  PAKDD [A], 20% acceptance rate, Delhi, India, 05/2021.
  [bibtex]

• Scholarly Text Classification with Sentence BERT and Entity Embeddings,
  Guangyuan Piao,
  SDPRA Workshop at PAKDD, Delhi, India, 05/2021.
  [bibtex] [code]

• Partially Observable Markov Decision Process Modelling for Assessing Hierarchies,
  Weipeng Huang, Guangyuan Piao, Raul Moreno Salinas, Neil Hurley,
  ACML [Best Student Paper Award], 33% acceptance rate, Bangkok, Thailand, 11/2020.
  [bibtex]

• Regression-enhanced Random Forests with Personalized Patching for COVID-19 Retweet Prediction,
  Guangyuan Piao, Weipeng Huang,
  CIKM AnalytiCup, 10/2020.
  [bibtex] [code]

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

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

• Mining User Interests from Social Media,
  Fattane Zarrinkalam, Stefano Faralli, Guangyuan Piao and Ebrahim Bagheri,
  IJCAI Tutorial [A*], 07/2020.
  [bibtex] [video]

• Env2Vec: Accelerating VNF Testing via Deep Learning,
  Guangyuan Piao, Pat Nicholson, Diego Lugones,
  EuroSys [A], 18% acceptance rate, Crete, Greece, 04/2020.
  [bibtex] [video] [ad video]

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

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

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

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

• A Study of the Similarities of Entity Embeddings Learned from Different Aspects of a Knowledge Base for ItemRecommendations,
  Guangyuan Piao and John G. Breslin,
  Workshop on DL for KGs and Semantic Technologies at ESWC [Best Paper Award], Crete, Greece, 06/2018.
  [bibtex]

• Learning to Rank Tweets with Author-based Long Short-Term Memory Networks,
  Guangyuan Piao and John G. Breslin,
  ICWE [B], Caceres, Spain, 06/2018.
  [bibtex]

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

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

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

• Factorization Machines Leveraging Lightweight Linked Open Data-enabled Features for Top-N Recommendations ,
  Guangyuan Piao and John G. Breslin,
  WISE [A], 25% acceptance rate, Moscow, Russia, 07/10/2017.
  [bibtex]

• Leveraging Followee ListMemberships for Inferring User Interests for Passive Users on Twitter,
  Guangyuan Piao and John G. Breslin,
  Hypertext [A], 27% acceptance rate, Prague, Czech Republic, 04/07/2017.
  [bibtex] [ppt]

• Inferring User Interests for Passive Users on Twitter by Leveraging Followee Biographies,
  Guangyuan Piao and John G. Breslin,
  ECIR [A], 26.7% acceptance rate, Aberdeen, UK, 08/04/2017.
  [bibtex] [ppt]

• Interest Representation, Enrichment, Dynamics, and Propagation: A Study of the Synergetic Effect of Different User Modeling Dimensions for Personalized Recommendations on Twitter,
  Guangyuan Piao and John G. Breslin,
  EKAW [B], 17.5% acceptance for long presentations, Bologna, Italy, 19/11/2016.
  [bibtex] [ppt]

• User Modeling on Twitter with WordNet Synsets and DBpedia Concepts for Personalized Recommendations,
  Guangyuan Piao and John G. Breslin,
  CIKM [A], 23.5% acceptance rate for short, Indianapolis, USA, 24/10/2016.
  [bibtex] [ppt]

• Exploring Dynamics and Semantics of User Interests for User Modeling on Twitter for Link Recommendations,
  Guangyuan Piao and John G. Breslin,
  SEMANTiCS [Best Paper Award], 21% acceptance rate, Leipzig, Germany, 12/09/2016.
  [bibtex] [ppt]

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

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

• Analyzing Aggregated Semantics-enabled User Modeling on Google+ and Twitter for Personalized Link Recommendations,
  Guangyuan Piao and John G. Breslin,
  UMAP [B], 28% acceptance rate for short, Halifax, Canada, 13/07/2016.
  [bibtex] [ppt] [travel report]

• Measuring Semantic Distance for Linked Open Data-enabled Recommender Systems ,
  Guangyuan Piao and John G. Breslin,
  SAC [B], 24% acceptance rate, Pisa, Italy, 04/04/2016.
  [bibtex] [ppt] [travel report] [code]

• Computing the Semantic Similarity of Resources in DBpedia for Recommendation Purposes,
  Guangyuan Piao and John G. Breslin,
  JIST [Best Paper Candidate], 33% acceptance rate, Yichang, China, 12/11/2015.
  [bibtex] [ppt] [travel report]