My research interests generally include machine learning, data analysis, deep learning, and recommender system, with an emphasis on designing new algorithms and models for managing and mining social and urban spatio-temporal data.

Recently, I am focusing on the following research directions:

• Data analytics and machine learning (e.g., deep learning and AI, recommender and filtering systems, interpretability of deep models, Web personalization)
• Understanding multi-modal content (e.g., natural language processing, text mining, image processing)
• Efficient data processing (e.g., database systems, indexing and query optimization)
• Applications (e.g., urban computing systems, social media)

• WULFA Merit Award, Wilfrid Laurier University, 2018
• NSERC Individual Discovery Grant, 2018-2023
• NSFC Research Grant, General Program, 2016-2019
• NSFC Research Grant, Youth Program, 2009-2012

I am looking for highly-motivated undergraduate and graduate students to work with me on the exciting area of machine learning and recommender systems. I also have open Postdoctoral Positions to investigate underlying theory and algorithms in deep learning, big data analytics, social networks, and recommender systems.

Journal Papers

• Chen, M., Zhao, Y., Liu, Y., Yu, X., Zheng, K.: Modeling Spatial Trajectories with Attribute Representation Learning, in IEEE Transactions on Knowledge and Data Engineering, DOI:10.1109/TKDE.2020.3001025, 2020.
• Chen, M., Zuo, Y., Jia, X*, Liu, Y., Yu, X., Zheng, K.: CEM: A Convolutional Embedding Model for Predicting Next Locations, in IEEE Transactions on Intelligent Transportation Systems, DOI: 10.1109/TITS.2020.2983647, 2020.
• Tal, O.*, Liu, Y.: A Joint Deep Recommendation Framework for Location-Based Social Networks, in Complexity, 2926749:1-2926749:11, 2019.
• Tal, O.*, Liu, Y., Huang, J., Yu, X., Aljbawi, B.*: Neural Attention Frameworks for Explainable Recommendation, in IEEE Transactions on Knowledge and Data Engineering (TKDE), DOI: 10.1109/TKDE.2019.2953157, 2019.
• Chen, M., Yu, X., Liu, Y.: TraLFM: Latent Factor Modeling of Traffic Trajectory Data, in IEEE Transactions on Intelligent Transportation Systems 20 (12), 4624-4634, 2019.
• Yu, Z., Abraham, A., Yu, X., Liu, Y., Zhou, Z., Ma, K.: Improving the effectiveness of keyword search in databases using query logs, in Eng. Appl. Artif. Intell., 81: 169-179, 2019.
• Chen, M., Jia, X.*, Gorbonos, E.*, T. Hoang, C., Yu, X., Liu, Y: Eating healthier: Exploring nutrition information for healthier recipe recommendation, in Information Processing & Management, https://doi.org/10.1016/j.ipm.2019.05.012, 2019.
• Chen, M., Yu, X., Liu, Y.: MPE: a mobility pattern embedding model for predicting next locations, in World Wide Web, 22(6): 2901-2920, 2018.
• Chen, M., Yu, X., Liu, Y.: PCNN: Deep Convolutional Networks for Short-Term Traffic Congestion Prediction, in IEEE Trans. Intelligent Transportation Systems 19(11): 3550-3559, 2018.
• Chen, B.*, Lv, Z., Yu, X., Liu, Y.: Sliding Window Top-K Monitoring over Distributed Data Streams, in Data Science and Engineering 2(4): 289-300, 2017.
• , X., Yu, Z., Liu, Y., Shi, H.:CI-Rank: Collective importance ranking for keyword searching databases, in Inf. Sci. 384: 1-20, 2017.
• Chen, M.*, Zhang, L.*, Yu, X., Liu, Y.: Weighted Co-Training for Cross-Domain Image Sentiment Classification, in J. Comput. Sci. Technol, 32(4): 714-725, 2017.
• Yang, C., Yu, X., Liu, Y., Nie, Y.*, Wang Y.*: Collaborative filtering with weighted opinion aspects, in Neurocomputing, 210: 185-196, 2016.
• Chen, M.*, Yu, X., Liu, Y.: Mining Object Similarity for Predicting Next Locations, in J. Comput. Sci. Technol, 31(4): 649-660, 2016.
• Yu, Z., Liu, Y., Yu, X., Pu, K.: Scalable Distributed Processing of K Nearest Neighbor Queries over Moving Objects, in IEEE Transactions on Knowledge and Data Engineering, 27(5): 1383-1396, 2015.
• Chen M.*, Yu, X.,Liu, Y.: Mining Moving Patterns for Predicting Next Location, in Information Systems, Vol. 54: 156-168, December 2015.
• Liu, Y., Yu, X., An, A., Huang, X.: Riding the tide of sentiment change: sentiment analysis with evolving online reviews, in World Wide Web, 16(4): 477-496, 2013.
• Yu, X., Liu, Y., Huang, X. and An, A.: Mining Online Reviews for Predicting Sales Performance: A Case Study in the Movie Domain, in IEEE Transactions on Knowledge and Data Engineering, 24(4):720-734, 2012.
• Liu, Y., Yu, X., Huang, X. and An, A.: Combining Integrated Sampling with SVM Ensembles for Learning from Imbalanced Datasets, in Information Processing & Management, 47(4):617-631, 2011.
• Liu, Y., Huang, X. and An, A.: Personalized Recommendation with Adaptive Mixture of Markov Models, Journal of the American Society for Information Science and Technology (JASIST) - Mining Web Resources for Enhancing Information Retrieval. Vol.58, No.12, pp.1851 – 1870, 2007.

Peer-reviewed Conference Papers

• Yu, Z., Yu, X., Koudas, N., Liu, Y., Li, Y., Chen, Y., Yang, D.: Distributed Processing of k-Shortest Path Queries over Dynamic Road Networks. SIGMOD Conference 2020: 665-679.
• Gorbonos, E.*, Liu, Y., Hong, C.: NutRec: Nutrition Oriented Online Recipe Recommender in IEEE/WIC/ACM International Conference on Web Intelligence, 2018: 25-32.
• Guo, D.*, Chen, M., Yu, X., Liu, Y.: Short-term Traffic Flow Forecasting Using Transfer Ratio and Road Similarity, in IJCNN 2018: 1-7.
• Wang, Y.*, Chen, M., Yu, X., Liu, Y.:LCE: A Location Category Embedding Model for Predicting the Category Labels of POIs, in ICONIP (5) 2017: 710-720.
• Yin, H.*, Liu, Y.: Loc2Vec: Semantic Analysis of Spatial Temporal Trajectory in LBSNs, in Proceedings of the 5th National Conference on Social Media Processing, Oct. 2016. (Best Paper Award)
• Zhou, J., Liu, Y., Yu, Z.: Improving the Effectiveness of Keyword Search in Databases Using Query Logs, in Proceedings of the 16th International Conference on Web-Age Information Management (WAIM) 2015: 193-206. (Best Paper Award)
• Chen, M.*, Liu, Y., Yu, X.: Predicting Next Locations with Object Clustering and Trajectory Clustering, in Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2015: 344-356. (Runner up for Best Paper Award)
• Lv, L., Chen, M.*, Liu, Y, Yu, X.: A Plane Moving Average Algorithm for Short-Term Traffic Flow Prediction, in Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2015: 357-369.
• Liu, Y., Yu, X., Liu, B., Chen, Z.*: Sentence-Level Sentiment Analysis in the Presence of Modalities, in Proceedings of Conference on Intelligent Text Processing and Computational Linguistics (CICLing) 2014: 1-16.
• Yang, C., Yu, X., Liu, Y.: Continuous KNN Join Processing for Real-time Recommendation in IEEE International Conference on Data Mining (ICDM), 2014.
• Nie, Y.*, Liu, Y, Yu, X.: Weighted aspect-based collaborative filtering, in Proceedings of the34th Annual ACM Special Interest Group on Information Retrieval(SIGIR), 2014.
• Wang, Y.*,Liu, Y., Yu, X.: Collaborative Filtering with Aspect-based Opinion Mining: A Tensor Factorization Approach, in Proceedings of the IEEE International Conference on Data Mining (ICDM), 2012.
• Liu, Y., Yu, X., Huang, X. and An, A.: S-PLSA+: Adaptive Sentiment Analysis with Ap-plication to Sales Performance Prediction, in Proceedings of ACM Special Interest Group on Information Retrieval (SIGIR), 2010.
• Yu, X., Liu, Y., Huang, X., An, A.: A Quality-Aware Model for Sales Prediction Using Reviews, in Proceedings of the 19th International World Wide Web Conference (WWW), 2010.
• Liu, Y., Huang, X., An, A., and Yu., X: Predicting the Helpfulness of Online Reviews, in the Proceedings of 8th IEEE International Conference on Data Mining (ICDM), 2008. pp.443-452.
• Yu, X., and Liu, Y.: Reasoning about Similarity Queries in Text Retrieval Tasks, in Proceedings of the 17th International World Wide Web Conference (WWW), 2008. pp.1227-1228.
• Liu, Y., Huang, X., An, A., and Yu., X: ARSA: A Sentiment-Aware Model for Predicting Sales Performance Using Blogs, in SIGIR, 2007. pp. 607-614.
• Huang, J., Huang, Y., Wen, M., An, A., Liu, Y., and Poon, J.: Applying Data Mining to Pseudo-Relevance Feedback for High Performance Text Retrieval, in ICDM, 2006. pp.295-306.

HQPs are marked with *.

• CP640 Machine Learning
• CP610 Data Analysis
• CP421 Data Mining
• CP423 Text Retrieval and Search Engines
• CP322 Machine Learning
• CP213 Object-oriented Programming