Foundations and Theory
Core models, algorithms, theory, and scalable methods for mining complex and large-scale data.
This page isolates the technical scope of the conference so visitors can read it as a coherent research summary, not as a fragment buried inside the homepage.
These entries can be refined into the official ICDM 2028 call for papers once the program chairs finalize wording.
Core models, algorithms, theory, and scalable methods for mining complex and large-scale data.
Learning paradigms for structured, high-dimensional, uncertain, and continuously evolving datasets.
Text, graph, web, time series, semi-structured, multimedia, spatial, and streaming sources.
Parallel, distributed, privacy-aware, secure, and federated infrastructures for data mining workloads.
Interactive analytics, personalization, interpretability, and decision support from mined knowledge.
Mining signals and behavior in connected systems, infrastructure, mobility, and time-evolving networks.
LLM-supported mining workflows, reasoning over data, retrieval augmentation, and multimodal agents.
Health, climate, finance, engineering, social science, education, and industry-facing data products.