Area of research
Information Systems · Computer Vision and Pattern Recognition
Research interest
Research focused on Latent Dirichlet allocation and Artificial intelligence, with related work in Discriminative model, Sparse approximation, Anomaly detection. Notable publications include 'Automated classification of software change messages by semi-supervised Latent Dirichlet Allocation', 'A comprehensive comparative study of clustering-based unsupervised defect prediction models', and 'Which Non-functional Requirements Do Developers Focus On? An Empirical Study on Stack Overflow Using Topic Analysis'.
A Feature Distribution Smoothing Network Based on Gaussian Distribution for QoS Prediction
Postmortem Interval Estimation Using Protein Chip Technology Combined with Multivariate Analysis Methods.
Deep Attentive Anomaly Detection for Microservice Systems with Multimodal Time-Series Data
Quality Assurance for Automated Commit Message Generation
A comprehensive comparative study of clustering-based unsupervised defect prediction models
Improving Log-Based Anomaly Detection with Component-Aware Analysis
Automated change-prone class prediction on unlabeled dataset using unsupervised method
Improved hypergraph regularized Nonnegative Matrix Factorization with sparse representation
A component recommender for bug reports using Discriminative Probability Latent Semantic Analysis
Duplication Detection for Software Bug Reports based on Topic Model
Which Non-functional Requirements Do Developers Focus On? An Empirical Study on Stack Overflow Using Topic Analysis
Automatically classifying software changes via discriminative topic model: Supporting multi-category and cross-project
Class specific sparse representation for classification
Automated classification of software change messages by semi-supervised Latent Dirichlet Allocation