Publications

Journals

  1. VSE-fs: Fast Full-Sample Visual Semantic Embedding[PDF]
    S. Zhai, G. Guo*, F. Yuan, Y. Liu, X. Wang
    IEEE Intelligent Systems (IF: 4.464), accepted, 2020.
  2. Exploiting Review Embedding and User Attention for Item Recommendation[PDF]
    Y. Sun, G. Guo*, X. Chen, P. Zhang, X. Wang
    Knowledge and Information Systems (IF: 2.397), accepted, 2020.
  3. Multi-facet User Preference Learning for Fine-grained Item Recommendation[PDF]
    X. Zhou, G. Guo*, Z. Sun, Y. Liu
    Neurocomputing (IF: 4.072), accepted, 2020.
  4. Fast Discrete Factorization Machine for Personalized Item Recommendation[PDF]
    S. Qu, G. Guo*, Y. Liu, Y. Yao, W. Wei
    Knowledge-based Systems (IF: 5.101), accepted, 2020.
  5. Multi-level Coupling Network for Non-IID Sequential Recommendation[PDF]
    Y. Sun, G. Guo*, X. He, X. Liu
    IEEE Access (IF: 4.098), accepted, 2020.
  6. Visual Semantic Image Recommendation[PDF]
    G. Guo, Y. Meng, Y. Zhang, C. Han, Y. Li
    IEEE Access (IF: 3.557), 7, 33424 - 33433, Feb 2019.
  7. PCCF: Periodic and Continual Temporal Co-Factorization for Recommender Systems[PDF]
    G. Guo, F. Zhu, S. Qu, X. Wang
    Information Sciences (IS, IF: 4.832), 436-437, 56-73, Apr 2018.
  8. Search Engine based Proper Privacy Protection Scheme[PDF]
    G. Guo, T. Yang, Y. Liu
    IEEE Access (IF: 3.557), 6, 78551-78558, Dec 5, 2018.
  9. BPRH: Bayesian Personalized Ranking for Heterogeneous Implicit Feedback[PDF]
    H. Qiu, Y. Liu*, G. Guo, Z. Sun, J. Zhang, H. T. Nguyen
    Information Sciences (IS, IF: 4.832), 453, 80-98, Apr 2018.
  10. Factored Similarity Models with Social Trust for Top-N Item Recommendation[PDF | Code]
    G. Guo, J. Zhang, F. Zhu, X. Wang
    Knowledge-based Systems (KBS, IF: 4.529), 122, 17-25, Apr 15, 2017.
  11. Resolving Data Sparsity by Multi-type Auxiliary Implicit Feedback for Recommender Systems[PDF]
    G. Guo, H. Qiu, Z. Tan, Y. Liu, J. Ma, X. Wang
    Knowledge-based Systems (KBS, IF: 4.529), 138, 202-207, Dec 15, 2017.
  12. Leveraging Multi-actions to Improve Medical Personalized Ranking for Collaborative Filtering[PDF]
    S. Gao, G. Guo*, R. Li, Z. Wang
    Journal of Healthcare Engineering (IF: 0.965), Oct 3, 2017.
  13. Measuring Similarity of Users with Qualitative Preferences for Service Selection
    H. Wang, H. Wang, G. Guo, Y. Tang, J. Zhang
    Knowledge and Information Systems (KIS, IF: 2.004), 51(2), 561-594, May 2017.
  14. A Novel Recommendation Model Regularized with User Trust and Item Ratings[PDF | Code]
    G. Guo, J. Zhang, N. Yorke-Smith
    IEEE Transactions on Knowledge and Data Engineering (TKDE, IF: 3.438), 28(7), 1607-1620, 2016.
    The source codes of TrustSVD++ can be downloaded here, which is based on a previous version (v1.3) of LibRec.
    You may refer to the implementation of TrustSVD in LibRec for adapting and using TrustSVD++ in the new version.
  15. A Novel Evidence-based Bayesian Similarity Measure for Recommender Systems
    G. Guo, J. Zhang, N. Yorke-Smith
    ACM Transactions on the Web (TWEB, IF: 1.526), 10(2), 8:1-8:30, 2016.
  16. Leveraging Multiviews of Trust and Similarity to Enhance Cluster-based Recommender Systems[PDF]
    G. Guo, J. Zhang, N. Yorke-Smith
    Knowledge-Based Systems (KBS, IF: 3.325), 74(0), pp. 14-27, 2015.
  17. Multi-Faceted Trust and Distrust Prediction for Recommender Systems[PDF]
    H. Fang, G. Guo*, J. Zhang
    Decision Support Systems (DSS, IF: 2.604), 71(0), pp. 37-47, 2015.
  18. Integrating Trust with User Preference for Effective Web Service Composition
    H. Wang, B. Zou, G. Guo, J. Zhang, D. Yang
    IEEE Transactions on Services Computing (TSC, IF: 2.365), accepted, 2015.
  19. Merging Trust in Collaborative Filtering to Alleviate Data Sparsity and Cold Start[PDF]
    G. Guo, J. Zhang, D. Thalmann
    Knowledge-Based Systems (KBS, IF: 2.947), 57(0), pp. 57-68, 2014.
  20. Leveraging Prior Ratings for Recommender Systems in E-Commerce[PDF]
    G. Guo, J. Zhang, D. Thalmann, N. Yorke-Smith
    Electronic Commerce Research and Applications (ECRA, IF: 1.482), 13(6), pp. 440-455, 2014.
  21. Opinions of People: Factoring in Privacy and Trust[PDF]
    A. Basu, J. Vaidya, J.C. Corena, S. Kiyomoto, S. Marsh, G. Guo, J. Zhang, Y. Miyake
    ACM SIGAPP Applied Computing Review, 14(3), pp. 7-21, 2014.

Conferences

  1. Leveraging Title-Abstract Attentive Semantics for Paper Recommendation
    G. Guo, B. Chen, X. Zhang, Z. Liu, Z. Dong, X. He
    Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (20.6% acceptance, 1591/7737)
  2. BiGAN: Collaborative Filtering with Bidirectional Generative Adversarial Networks
    R. Ding, G. Guo*, B. Chen, X. Yang
    Proceedings of the 20th SIAM International Conference on Data Mining (SDM), 2020. (24% acceptance, 75/312)
  3. Future Data Helps Training: Modelling Future Contexts for Session-based Recommendation
    F. Yuan, G. Guo*, C. He, etc.
    Proceedings of the 29th International Conference on the Web (WWW), 2020. (19% acceptance, 219/1129)
  4. Modelling Temporal Dynamics and Repeated Behaviors for Recommendation
    X. Zhou, Z. Sun, G. Guo*, etc.
    Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020. (21% acceptance, 131/628)
  5. Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation
    G. Guo, S. Ouyang, X. He, F. Yuan, X. Liu
    Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. (17.9% acceptance, 850/4752)
  6. Discrete Trust-aware Matrix Factorization for Fast Recommendation
    G. Guo, E. Yang, L. Shen, X. Yang, X. He
    Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. (17.9% acceptance, 850/4752)
  7. Multi-Hop Path Queries over Knowledge Graphs with Neural Memory Networks
    Q. Wang, H. Yin, W. Wang, Z. Huang, G. Guo, Q.V.H. Nguyen
    Proceedings of the 24th International Conference on Database Systems for Advanced Applications (DASFAA), 2019.
  8. Approximating Word Ranking and Negative Sampling for Word Embedding
    G. Guo, S. Ouyang, F. Yuan, X. Wang
    Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018. (20% acceptance, 710/3470)
  9. VSE-ens: Visual-Semantic Embeddings with Efficient Negative Sampling
    G. Guo, S. Zhai, F. Yuan, Y. Liu, X. Wang
    Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018.
  10. fBGD: Learning Embeddings from Positive-Only Data Without Sampling
    F. Yuan,X. Xin, X. He, G. Guo, W.Zhang, T. Chua, J. Jose
    Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence (UAI), 2018.
  11. Team Expansion in Collaborative Environment
    L. Zhao, Y. Yao, G. Guo, H. Tong, F. Xu, J. Lu
    Proceedings of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 713-725, 2018.
  12. Multi-view Visual Bayesian Personalized Ranking from Implicit Feedback
    H. Luo, X. Zhang, B. Chen, G. Guo
    Proceedings of the ACM Conference on User Modeling, Adaptation, and Personalization (UMAP), 2018. (extended abstract)
  13. LFSF: Latent Factor-Based Similarity Framework and Its Application for Collaborative Recommendation
    L. He, Z. Tan, G. Guo, Q. Chang, D. Wu
    Proceedings of the 19th Pacific-Rim Conference on Multimedia (PCM), pp. 744-754, 2018.
  14. BoostFM: Boosted Factorization Machines for Top-N Feature-based Recommendation
    F. Yuan, G. Guo, J. Jose, L. Chen, H. Yu, W. Zhang
    Proceedings of the 22nd Annual Meeting of the Intelligent User Interfaces Community and Serves (IUI), 2017.
  15. Learning Hierarchical Category Influence on both Users and Items for Effective Recommendation
    Z. Sun, G. Guo, J. Zhang
    Proceedings of the 32nd ACM Symposium On Applied Computing (SAC), 2017.
  16. A Unified Latent Factor Model for Effective Category-Aware Recommendation
    Z. Sun, G. Guo, J. Zhang, C. Xu
    Proceedings of the 25th International Conference on User Modeling, Adaptation and Personalization (UMAP), 2017. (extended abstract)
  17. An Identity Management System Based on Blockchain
    Y. Liu, Z. Zhao, G. Guo, X. Wang, Z. Tan, S. Wang
    Proceedings of the 15th International Conference on Privacy, Security and Trust (PST), 2017
  18. A Reputation Model for Aggregating Ratings based on Beta Distribution Function
    Y. Liu, U. S. Chitawa, G. Guo, X. Wang, Z. Tan, S. Wang
    Proceedings of the 2nd International Conference on Crowd Science and Engineering (ICCSE), pp. 77-81, 2017
  19. LambdaFM: Learning Optimal Ranking with Factorization Machines Using Lambda Surrogates
    F. Yuan, G. Guo, J. Jose, W. Zhang, L. Chen, H. Yu
    Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM, 165/935=17.65%), pp. 227-236, 2016.
  20. Optimizing Factorization Machines for Top-N Context-Aware Recommendations
    F. Yuan, G. Guo, J. Jose, W. Zhang, L. Chen, H. Yu
    Proceedings of the 17th International Conference on Web Information Systems Engineering (WISE), pp. 278-293, 2016.
  21. Joint Geo-Spatial Preference and Pairwise Ranking for Point-of-Interest Recommendation
    F. Yuan, J. Jose, G. Guo, L. Chen, H. Yu, R. Alkhawaldeh
    Proceedings of the 28th International Conference on Tools with Artificial Intelligence (ICTAI), 2016. (best student paper)
  22. Effective Recommendation with Category Hierarchy
    Z. Sun, G. Guo, J. Zhang
    Proceedings of the 24th International Conference on User Modeling, Adaptation and Personalization (UMAP), 2016. (extended abstract)
  23. TBPR: Trinity Preference based Bayesian Personalized Ranking for Multivariate Implicit Feedback
    H. Qiu, G. Guo, J. Zhang, H. Nguyen, Z. Sun, Y. Liu
    Proceedings of the 24th International Conference on User Modeling, Adaptation and Personalization (UMAP), 2016. (extended abstract)
  24. TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings[PDF, Code]
    G. Guo, J. Zhang, N. Yorke-Smith
    Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI, acceptance rate: 26.67%), 2015.
  25. LibRec: A Java Library for Recommender Systems[PDF, Code]
    G. Guo, J. Zhang, Z. Sun, N. Yorke-Smith
    Proceedings of the 23rd International Conference on User Modeling, Adaptation and Personalization (UMAP), 2015. (demo paper)
  26. Exploiting Implicit Item Relationships for Recommender Systems[PDF]
    Z. Sun, G. Guo, J. Zhang
    Proceedings of the 23rd International Conference on User Modeling, Adaptation and Personalization (UMAP), 2015.
  27. Optimal and Effective Web Service Composition with Trust and User Preference
    H. Wang, B. Zou, G. Guo, J. Zhang, Z. Yang
    Proceedings of the 22nd IEEE International Conference on Web Services (ICWS, acceptance rate: 20%), pp. 329-336, 2015.
  28. ETAF: An Extended Trust Antecedents Framework for Trust Prediction[PDF, Slides]
    G. Guo, J. Zhang, D. Thalmann, N. Yorke-Smith
    Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM, acceptance rate: 18%), pp. 540-547, 2014.
  29. From Ratings to Trust: an Empirical Study of Implicit Trust in Recommender Systems[PDF, Slides]
    G. Guo, J. Zhang, D. Thalmann, A. Basu, N. Yorke-Smith
    Proceedings of the 29th ACM Symposium on Applied Computing (SAC), pp. 248-253, 2014.
  30. Privacy Preserving Trusted Social Feedback[PDF]
    A. Basu, J.C. Corena, S. Kiyomoto, S. Marsh, J. Vaidya, G. Guo, J. Zhang, Y. Miyake
    Proceedings of the 29th ACM Symposium on Applied Computing (SAC), pp. 1706-1711, 2014.
  31. A Hybrid Recommender System based on Material Concepts with Difficulty Levels[PDF]
    G. Guo, M. H. Anjorin, B. S. Lee
    Proceedings of the 21st International Conference on Computers in Education (ICCE), pp. 90-96, 2013.
  32. Combining Recommender and Reputation Systems to Produce Better Online Advice[PDF]
    A. Josang, G. Guo, M. S. Pini, F. Santini, Y. Xu
    Proceedings of the 10th International Conference on Modeling Decisions for Artificial Intelligence (MDAI), pp. 126-138, 2013.
  33. Prior Ratings: A New Information Source for Recommender Systems in E-Commerce[PDF, Poster]
    G. Guo, J. Zhang, D. Thalmann, N. Yorke-Smith
    Proceedings of the 7th ACM Conference on Recommender Systems (RecSys), pp. 383-386, 2013.
  34. Integrating Trust and Similarity to Ameliorate the Data Sparsity and Cold Start for Recommender Systems[PDF, Slides]
    G. Guo
    Proceedings of the 7th ACM Conference on Recommender Systems (RecSys), pp. 451-454, 2013.
  35. A Novel Bayesian Similarity Measure for Recommender Systems[PDF, Poster, Code]
    G. Guo, J. Zhang, N. Yorke-Smith
    Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), pp. 2619-2625, 2013.
    Note: Although the code is dependent on an obsolete package, the implementation logic may be still useful for some others. We may integrate the Bayesian similarity into LibRec some time.
  36. Improving the Performance of Recommender Systems by Alleviating the Data Sparsity and Cold Start Problems[PDF]
    G. Guo
    Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), pp. 3217-3218, 2013.
  37. A New Recommender System for 3D E-Commerce: An EEG Based Approach[PDF]
    G. Guo, M. Elgendi
    Proceedings of the 2013 International Conference on Innovation and Information Management (ICIIM), pp. 61-65, 2013.
  38. A Simple but Effective Method to Incorporate Trusted Neighbors in Recommender Systems[PDF]
    G. Guo, J. Zhang, D. Thalmann
    Proceedings of the 20th International Conference on User Modeling, Adaptation and Personalization (UMAP), pp. 114-125, 2012.
  39. Resolving Data Sparsity and Cold Start in Recommender Systems[PDF]
    G. Guo
    Proceedings of the 20th International Conference on User Modeling, Adaptation and Personalization (UMAP), pp. 361-364, 2012.
  40. WCP-nets: A Weighted Extension to CP-nets for Web Service Selection[PDF]
    H. Wang, J. Zhang, W. Sun, H. Song, G. Guo, X. Zhou
    Proceedings of the 10th International Conference on Service Oriented Computing (ICSOC), pp. 298-312, 2012.
  41. Service Selection based on Similarity Measurement for Conditional Qualitative Preference[PDF]
    H. Wang, J. Zhang, H. Wang, Y. Tang, G. Guo
    Proceedings of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pp. 612-619, 2012.
  42. Improving PGP Web of Trust through the Expansion of Trusted Neighborhood[PDF, Slides]
    G. Guo, J. Zhang, J. Vassileva
    Proceedings of the 2011 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pp. 489-494, 2011.

Workshops

  1. IFUP: Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization
    F. Zhu, Y. Zhang, N. Yorke-Smith, G. Guo, X. Chen
    Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), pp. 804-805, 2018.
  2. Preface: Papers and Research from the 2016 International Workshop IFUP[PDF]
    G. Guo, R. Burke, F. Zhu, N. Yorke-Smith
    Proceedings of the 2016 International Workshop on Multi-dimension Information Fusion for User Modeling and Personalisation (UMAP IFUP), 2016.
  3. Reducing Information Overload in Social Networks through Streamlined Presentation: a Study of Content-centric and Person-centric Contexts[PDF]
    R. Cohen, N. Sardana, K. Rahim, D.Y. Lam, M. Li, O. Maccarthy, E. Woo, G. Guo
    Proceedings of the 3rd International Workshop on Incentives and Trust in E-Commerce (AAAI WIT-EC), 2014.
  4. Qualitative and Quantitative Preferences Based Web Service Composition by Integrating with Trust
    H. Wang, B. Zou, G. Guo
    Proceedings of the 2nd International Workshop on Incentives and Trust in E-Commerce (IJCAI WIT-EC), 2013.
  5. Recommending Messages to Users in Social Networks: a Cross-Site Study[PDF]
    R. Cohen, N. Sardana, K. Rahim, D. Y. Lam, M. Li, O. Maccarthy, E. Woo, J. Zhang, G. Guo
    Proceedings of the 12th International Conference on Machine Learning and Applications (ICMLA Bigdata), pp. 445-450, 2013.

Reports

  1. Deep Learning-based Sequential Recommender Systems: Concepts, Algorithms, and Evaluations
    H. Fang, G. Guo, D. Zhang, Y. Shu
    Tutorial, The 19th International Conference on Web Engineering (ICWE), 2019.
  2. Exploiting Ratings and Trust to Resolve the Data Sparsity and Cold Start of Recommender Systems
    G. Guo
    Ph.D Thesis, School of Computer Engineering, Nanyang Technological University, 2014.

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