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SDM 2021 : SIAM International Conference on Data Mining (SDM)

SDM 2021 : SIAM International Conference on Data Mining (SDM)

Alexandria, Virginia , United States

Submission Deadline: Monday 05 Oct 2020

Conference Dates: Mar 25, 2021 - Mar 25, 2021

Research
Impact Score 4.10

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Ranking & Metrics Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.

Research Impact Score: 4.10
Contributing Best Scientists: 124
H5-index:
Papers published by Best Scientists 155
Research Ranking (Computer Science) 118

Conference Call for Papers

About the Conference

Sponsored by the SIAM Activity Group on Data Mining and Analytics.
This conference is held in cooperation with the American Statistical Association.

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.

Included Themes
Methods and Algorithms

Anomaly & Outlier Detection
Big Data & Large-Scale Systems
Classification & Semi-Supervised Learning
Clustering & Unsupervised Learning
Data Cleaning & Integration
Deep Learning & Representation Learning
Frequent Pattern Mining
Feature Extraction, Selection and Dimensionality Reduction
Mining Data Streams
Mining Graphs & Complex Data
Mining on Emerging Architectures & Data Clouds
Mining Semi Structured Data
Mining Spatial & Temporal Data
Mining Text, Web & Social Media
Online Algorithms
Optimization Methods
Parallel and Distributed Methods
Probabilistic & Statistical Methods
Scalable & High-Performance Mining
Other Novel Methods

Astronomy & Astrophysics
Automation & Process Control
Climate / Ecological / Environmental Science
Customer Relationship Management
Data Science
Drug Discovery
Finance
Genomics & Bioinformatics
Healthcare Management
High Energy Physics
Intelligence Analysis
Internet of Things
Intrusion & Fraud detection
Logistics Management
Recommendation
Risk Management
Social Network Analysis
Supply Chain Management
Other Emerging Applications

Ethics of Data Mining
Intellectual Ownership
Interestingness & Relevance
Privacy and Fairness Models
Privacy Preserving Data Mining
Risk Analysis and Risk Management
Transparency and Algorithmic Bias
User Interfaces and Visual Analytics
Other Human and Social Issues

Overview

Top Research Topics at SIAM International Conference on Data Mining?

  • Artificial intelligence (12.69%)
  • Optoelectronics (8.45%)
  • Data mining (8.20%)

The conference is organized to address concerns in the fields of Artificial intelligence, Optoelectronics, Data mining, Machine learning and Pattern recognition. The works on Artificial intelligence deal in particular with Cluster analysis.

What are the most cited papers published at the conference?

  • Clustering with Bregman Divergences (1347 citations)
  • R-MAT: A Recursive Model for Graph Mining (975 citations)
  • Learning from Time-Changing Data with Adaptive Windowing (829 citations)

Research areas of the most cited articles at SIAM International Conference on Data Mining:

The published articles tackle a plethora of topics, such as Data mining, Artificial intelligence, Cluster analysis, Machine learning and Pattern recognition. The published articles with studies in Data mining featured incorporate elements of Data stream, Set (abstract data type) and Data set. The published papers explore issues in Artificial intelligence which can be linked to other research areas like Exploit and Natural language processing.

What topics the last edition of the conference is best known for?

  • Artificial intelligence
  • Statistics
  • Machine learning

The previous edition focused in particular on these issues:

The conference primarily tackles Artificial intelligence, Machine learning, Pattern recognition, Algorithm and Data mining. Artificial intelligence research featured in it incorporates concerns from various other topics such as Task (project management) and Natural language processing. While work presented in the conference provided substantial information on Machine learning, it also covered topics in Crowdsourcing and Layer (object-oriented design).

SIAM International Conference on Data Mining facilitates discussions on Pattern recognition that incorporate concepts from other fields like Series (mathematics) and Curse of dimensionality. The Algorithm works featured in SIAM International Conference on Data Mining incorporate elements from Variable (computer science), Principal component analysis, Clustering high-dimensional data and Dimension (vector space). The subject of Deep learning, which is connected to the field of Consistency (database systems), serves as the foundation of the Artificial neural network research featured in it.

The most cited articles from the last conference are:

  • Deep Anomaly Detection on Attributed Networks. (84 citations)
  • Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles (83 citations)
  • Hierarchical attention networks for cyberbullying detection on the instagram social network (42 citations)

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Research.com

The top authors publishing at SIAM International Conference on Data Mining (based on the number of publications) are:

  • Philip S. Yu (48 papers) published 1 paper at the last edition the same number as at the previous edition,
  • Charu C. Aggarwal (31 papers) absent at the last edition,
  • 俊郎 平本 (31 papers) absent at the last edition,
  • Christos Faloutsos (28 papers) published 2 papers at the last edition, 2 less than at the previous edition,
  • 重佳 渡辺 (27 papers) absent at the last edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Research.com

Only papers with recognized affiliations are considered

The top affiliations publishing at SIAM International Conference on Data Mining (based on the number of publications) are:

  • IBM (124 papers) published 5 papers at the last edition, 7 less than at the previous edition,
  • Carnegie Mellon University (62 papers) published 3 papers at the last edition, 3 less than at the previous edition,
  • Tohoku University (55 papers) absent at the last edition,
  • University of Illinois at Chicago (49 papers) published 1 paper at the last edition the same number as at the previous edition,
  • University of Minnesota (45 papers) published 4 papers at the last edition, 1 more than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Research.com

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

Research.com

During the most recent 2019 edition, 4.55% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.00% were posted by at least one author from the top 10 institutions publishing at the conference. Another 11.90% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 23.81% of all publications and 39.29% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Research.com

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

Research.com

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

Research.com

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Research.com

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Previous Editions

SDM 2021 : SIAM International Conference on Data Mining (SDM)

Mar 25, 2021 - Mar 25, 2021

Alexandria, Virginia , United States, United States

SIAM International Conference on Data Mining

Apr 28, 2022 - Apr 30, 2022

Alexandria, VA , United States, United States

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