25 citations · 40 across the 5 of their papers we have counts for
7 papers
How to Ask the AI: A User Perspective Survey for Large Language Model Prompting
Yiqun Zhang, Yunfan Zhang, Mingjie Zhao +2
AI tools like ChatGPT and DeepSeek, powered by Large Language Models (LLMs), allow users to obtain instant and effective content responses simply by typing requests, such as ``plan…
Beyond Statistical Co-occurrence: Unlocking Intrinsic Semantics for Tabular Data Clustering
Mingjie Zhao, Yunfan Zhang, Yiqun Zhang +1
Deep Clustering (DC) has emerged as a powerful tool for tabular data analysis in real-world domains like finance and healthcare. However, most existing methods rely on data-level s…
Learning Unbiased Cluster Descriptors for Interpretable Imbalanced Concept Drift Detection
Yiqun Zhang, Zhanpei Huang, Mingjie Zhao +5
Unlabeled streaming data are usually collected to describe dynamic systems, where concept drift detection is a vital prerequisite to understanding the evolution of systems. However…
Learning Unified Distance Metric for Heterogeneous Attribute Data Clustering
Yiqun Zhang, Mingjie Zhao, Yizhou Chen +2
Datasets composed of numerical and categorical attributes (also called mixed data hereinafter) are common in real clustering tasks. Differing from numerical attributes that indicat…
Learning Order Forest for Qualitative-Attribute Data Clustering
Mingjie Zhao, Sen Feng, Yiqun Zhang +3
Clustering is a fundamental approach to understanding data patterns, wherein the intuitive Euclidean distance space is commonly adopted. However, this is not the case for implicit…
Break the Tie: Learning Cluster-Customized Category Relationships for Categorical Data Clustering
Mingjie Zhao, Zhanpei Huang, Yang Lu +4
Categorical attributes with qualitative values are ubiquitous in cluster analysis of real datasets. Unlike the Euclidean distance of numerical attributes, the categorical attribute…