Conference Information
SDM 2018 : SIAM International Conference on Data Mining
http://www.siam.org/meetings/sdm18/
Submission Date:
2017-10-06
Notification Date:
Conference Date:
2018-05-03
Location:
San Diego, California, USA
Years:
18
CCF: b   CORE: a   QUALIS: a2   Viewed: 20308   Tracked: 59   Attend: 5

Conference Location
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Call For Papers
Statement on Inclusiveness

As a professional society, SIAM is committed to providing an inclusive climate that encourages the open expression and exchange of ideas, that is free from all forms of discrimination, harassment, and retaliation, and that is welcoming and comfortable to all members and to those who participate in its activities. In pursuit of that commitment, SIAM is dedicated to the philosophy of equality of opportunity and treatment for all participants regardless of gender, gender identity or expression, sexual orientation, race, color, national or ethnic origin, religion or religious belief, age, marital status, disabilities, veteran status, field of expertise, or any other reason not related to scientific merit. This philosophy extends from SIAM conferences, to its publications, and to its governing structures and bodies. We expect all members of SIAM and participants in SIAM activities to work towards this commitment.

Description

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.

Themes

Methods and Algorithms

    Classification
    Clustering
    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 Image Data
    Mining on Emerging Architectures
    Text & Web Mining
    Optimization Methods
    Other Novel Methods

Applications

    Astronomy & Astrophysics
    High Energy Physics
    Recommender Systems
    Climate / Ecological / Environmental  Science
    Risk Management
    Supply Chain Management
    Customer Relationship Management
    Finance
    Genomics & Bioinformatics
    Drug Discovery
    Healthcare Management
    Automation & Process Control
    Logistics Management
    Intrusion & Fraud detection
    Bio-surveillance 
    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
Last updated by Dou Sun in 2017-09-23
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Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
20082824014.2%
20073023611.9%
20052184018.3%
20022503413.6%
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