Area of research
Computer Vision and Pattern Recognition · Information Systems
Research interest
Research focused on Latent Dirichlet allocation and Artificial intelligence, with related work in Discriminative model, Probabilistic latent semantic analysis, Pattern recognition (psychology). Notable publications include 'Automated classification of software change messages by semi-supervised Latent Dirichlet Allocation', 'Which Non-functional Requirements Do Developers Focus On? An Empirical Study on Stack Overflow Using Topic Analysis', and 'Automatically classifying software changes via discriminative topic model: Supporting multi-category and cross-project'.
LiF as a crack/defect healer and structural stabilizer for the spent lithium cobalt oxide
The mediating role of psychological capital on the relationship between perceived stress and self-directed learning ability in nursing students
Enhancing Cross-Modal Alignment in Multimodal Sentiment Analysis via Prompt Learning
Weakly Supervised Patch Label Inference Networks for Efficient Pavement Distress Detection and Recognition in the Wild
Deep Attentive Anomaly Detection for Microservice Systems with Multimodal Time-Series Data
Multi-Label Image Classification via Category Prototype Compositional Learning
A comprehensive investigation of the impact of feature selection techniques on crashing fault residence prediction models
Quality Assurance for Automated Commit Message Generation
Improving Log-Based Anomaly Detection with Component-Aware Analysis
Skeletal Shape Correspondence Through Entropy
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
On the effect of hyperedge weights on hypergraph learning
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