SDM 2018 : SIAM International Conference on Data Mining

  in Conferences   Posted on August 11, 2017

Conference Information

Submission Deadline Saturday 13 Oct 2018
Conference & Submission Link
Conference Dates May 3, 2018 - May 5, 2018
Conference Address San Diego, United States
Proceedings indexed by
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Google Scholar H5-index: 35
CORE 2017 Rating: A
Guide2Research Overall Ranking: 90
Category Rankings
Databases & Information Systems 17
Machine Learning & Arti. Intelligence 25

Conference Call for Papers

Data mining is the computational process for discovering valuable knowledge from data – the core of modern Data Science. It has enormous applications in numerous fields, including science, engineering, healthcare, business, and medicine. Typical datasets in these fields are large, complex, and often noisy. Extracting knowledge from these datasets requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms. These techniques in turn require implementations on high performance computational infrastructure that are carefully tuned for performance. Powerful visualization technologies along with effective user interfaces are also essential to make data mining tools appealing to researchers, analysts, data scientists and application developers from different disciplines, as well as usable by stakeholders.

SDM has established itself as a leading conference in the field of data mining and provides a venue for researchers who are addressing these problems to present their work in a peer-reviewed forum. SDM emphasizes principled methods with solid mathematical foundation, is known for its high-quality and high-impact technical papers, and offers a strong workshop and tutorial program (which are included in the conference registration). The proceedings of the conference are published in archival form, and are also made available on the SIAM web site.


Methods and Algorithms



Frequent Pattern Mining

Probabilistic & Statistical Methods

Graphical Models

Spatial & Temporal Mining

Data Stream Mining

Anomaly & Outlier Detection

Feature Extraction, Selection and Dimension Reduction

Mining with Constraints

Data Cleaning & Preprocessing

Computational Learning Theory

Multi-Task Learning

Online Algorithms

Big Data, Scalable & High-Performance Computing Techniques

Mining with Data Clouds

Mining Graphs

Mining Semi Structured Data

Mining Complex Datasets

Mining on Emerging Architectures

Text & Web Mining

Optimization Methods

Other Novel Methods


Astronomy & Astrophysics

High Energy Physics

Collaborative Filtering

Climate / Ecological / Environmental Science

Risk Management

Supply Chain Management

Customer Relationship Management


Genomics & Bioinformatics

Drug Discovery

Healthcare Management

Automation & Process Control

Logistics Management

Intrusion & Fraud detection


Sensor Network Applications

Social Network Analysis

Intelligence Analysis

Other Novel Applications & Case Studies

Human Factors and Social Issues

Ethics of Data Mining

Intellectual Ownership

Privacy Models

Privacy Preserving Data Mining & Data Publishing

Risk Analysis

User Interfaces

Interestingness & Relevance

Data & Result Visualization

Other Human Factors and Social Issues

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