6 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…
Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models
Zihua Yang, Xin Liao, Yiqun Zhang +1
Qualitative data are widespread in domains such as healthcare, marketing, and bioinformatics, where clustering offers a fundamental tool for pattern discovery. A core difficulty of…
CADM: Cluster-customized Adaptive Distance Metric for Categorical Data Clustering
Taixi Chen, Yiu-ming Cheung, Yiqun Zhang
An appropriate distance metric is crucial for categorical data clustering, as the distance between categorical data cannot be directly calculated. However, the distances between at…
Robust Categorical Data Clustering Guided by Multi-Granular Competitive Learning
Shenghong Cai, Yiqun Zhang, Xiaopeng Luo +3
Data set composed of categorical features is very common in big data analysis tasks. Since categorical features are usually with a limited number of qualitative possible values, th…
Categorical Data Clustering via Value Order Estimated Distance Metric Learning
Yiqun Zhang, Mingjie Zhao, Hong Jia +3
Clustering is a popular machine learning technique for data mining that can process and analyze datasets to automatically reveal sample distribution patterns. Since the ubiquitous…
Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering
Yiqun Zhang, Sen Feng, Pengkai Wang +5
Streaming data clustering is a popular research topic in data mining and machine learning. Since streaming data is usually analyzed in data chunks, it is more susceptible to encoun…