会议信息

DSA' 2026: International Conference on Data Science and Applications

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截稿日期:
2026-08-16 还有 2 天
通知日期:
2026-10-24
会议日期:
2026-11-27
会议地点:
Zurich, Switzerland
届数:
浏览: 17917   关注: 2   参加: 1

征稿

DSA' 2026 (International Conference on Data Science and Applications) is an academic conference held in Zurich, Switzerland on 2026-11-27. The paper submission deadline is 2026-08-16. Acceptance notifications are sent on 2026-10-24.

Scope 7th International Conference on Data Science and Applications (DSA 2026) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Science and Applications. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to. Topics of interest · Big Data Algorithms · Big Data Applications · Big Data Fundamentals · Big Data Management and Frameworks · Big Data Search · Big Data security · Bioinformatics · Biometrics · Consistent Data Model · Data and Knowledge Representation · Data Streams Mining, Graph Mining, Spatial Data Mining · Databases · Deep Learning · Exploring Data Analysis · Financial Modeling · Forecasting, Classification, Clustering · Image Analysis · Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge · Infrastructures for Big Data · Integrating Constraints and Knowledge in the KDD Process · Integration of Data Warehousing · Interactive Data Exploration / Visualization and Discovery · Knowledge Discovery Framework and Process, Including Pre- and Post-Processing · Languages and Interfaces for Data Mining · Learning in knowledge-intensive systems · Learning Problems · Machine Learning Applications · Mining from Low-Quality Information Sources · Mining Trends, Opportunities and Risks · OLAP and Data Mining · Parallel and Distributed Data Mining Algorithms · Pre-Processing Techniques, Visualization · Security and Information Hiding in Data Mining · Social Networks, Educational Data Mining · Statistical Techniques for Generation a Robust · Text video, Multimedia Data Mining, Web Mining
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