My Work.
Project
Journal Publications:
Conference Publications:
- Pattern Discovery and Disentanglement: Since the patterns identification process by traditional pattern discovery approach is based only on the deviation of their observed frequency of occurrences from their random default model, they could be entangled due to multiple unknown factors or their entwining source environments. Hence, the capability of discovering patterns from disentangled (statistically uncorrelated) associations is of primal importance to unveil knowledge embedded in the relational data set.
- Multivariate Time Series Analysis: A multivariate time series (MTS) is made up of data collected by monitoring the values of a set of temporarily related or interrelated variables over a period of time at successive instants spaced at uniform time intervals. Given a set of MTS, the problem of classification or clustering such data is concerned with discovering inherent groupings of the data according to how similar or dissimilar the time series are to each other.
Journal Publications:
- [J]Wong A K C., Zhou, P Y, & Butt, Z A, Pattern discovery and disentanglement on relational datasets. Sci Rep 11, 5688 (2021). https://doi.org/10.1038/s41598-021-84869-4
- [J] Zhou, P Y, and Wong A K C. "Explanation and prediction of clinical data with imbalanced class distribution based on pattern discovery and disentanglement." BMC Medical Informatics and Decision Making 21, no. 1 (2021): 1-15.
- [J] Zhou P Y, Sze-To A, Wong A K C. Discovery and disentanglement of aligned residue associations from aligned pattern clusters to reveal subgroup characteristics. BMC Medical Genomics. 11(S5), 2018. pp. 391-402. DOI: 10.1186/s12920-018-0417-z
- [J] Zhou P Y, Chan K C C, Ou X.J. Carol. Corporate Communication Network and Stock Price Movements: Insights From Data Mining. IEEE Transactions on Computational Social Systems. 5(2), 2018. pp. 391-402. DOI: 10.1109/TCSS.2018.2812703.
- [J] Zhou P Y, Lee E A, Sze-To A, Wong A K C. Revealing Subtle Functional Subgroups in Class A Scavenger Receptors by Pattern Discovery and Disentanglement of Aligned Pattern Clusters. Proteomes, 6(1), 2018. DOI: 10.3390/proteomes6010010.
- [J] Zhou P Y, Chan K C C. Fuzzy Feature Extraction for Multi-Channel EEG Classification. IEEE Transactions on Cognitive and Developmental Systems, 2016. DOI: 10.1109/TCDS.2016.2632130
- [J] Zhou P Y, Li G C, Wong A K C, An Effective Pattern Pruning and Summarization Method Retaining High Quality Patterns with High Area Coverage in Relational Datasets. IEEE Access, no.99, pp.1-1, DOI:10.1109/ACCESS.2016.2624418.
- [J] Liu Y, Liu Y, Wang C, Wang, X, Zhou P Y, Yu G, Chan K C C, What Strikes the Strings of Your Heart?-Multi-Label Dimensionality Reduction for Music Emotion Analysis via Brain Imaging. IEEE Transactions on Autonomous Mental Development, 2015.
Conference Publications:
- [C] Zhou, P Y, Wong A K C , Michalopoulos G. et al. "Revealing Common and Rare Patterns for Peritoneal Dialysis Eligibility Decisions with Association Discovery and Disentanglement." In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 927-933. IEEE, 2020.
- [C] Zhou P Y, Wong A K C, Sze-To A. Disentanglement of Protein Aligned Pattern Clusters to Reveal Subtle Functional Subgroups. Bioinformatics and Biomedicine (BIBM), 2017 IEEE International Conference on. IEEE, 2017.
- [C] Wong A K C, Zhou P Y,and Sze-To A., Discovering Deep Knowledge from Relational Data by Attribute-Value Association Proceedings of the 13th International Conference on Data Mining DMIN'17, pp. 51-57, 2017
- [C] Yu Yang, Pei-Yuan Zhou, Ruosong Yang, Kevin Chan, Jiannong Cao, “Mixed-features Extraction in Student Forum Discussion: Insights from Data Mining”, eLearning Forum Asia 2017 (eLFA 2017). June 15-17, 2017. Hong Kong, China.
- [C] Ruosong Yang, Pei-Yuan Zhou, Yu Yang, Kevin Chan, Jiannong Cao, “An Improved Natural Language Processing Approach for Learning Performance Prediction in Students’ Discussion Forum”, eLearning Forum Asia 2017 (eLFA 2017). June 15-17, 2017. Hong Kong, China.
- [C] Zhou P Y, Chan K C C, An unsupervised attribute clustering algorithm for unsupervised feature selection. Data Science and Advanced Analytics (DSAA), 2015 IEEE International Conference on. IEEE, 2015: 1-7.
- [C] Zhou P Y, Chan K C C, A Feature Extraction Method for Multivariate Time Series Classification Using Temporal Patterns Proc. Conf. on PAKDD2015, 2015.
- [C] Zhou P Y, Mo W, Tian C, et al. A two-stage classification framework for imbalanced data with overlapping labels. Service Operations and Logistics, and Informatics (SOLI), 2014 IEEE International Conference on. IEEE, 2014: 350-355.
- [C] Zhou P Y, Chan K C C, A Model-based Multivariate Time Series Clustering Algorithm", Proc. Conf. on PAKDD2014, Workshops on Pattern Mining and Application of Big Data (BigPMA), 2014
- [C] Zhou P Y, Lee E S A, Wong A K C. Regrouping of pattern clusters to reveal characteristics of distinct classes and related classes. Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on. IEEE, 2013: 55-61.