9th International Conference on Data Mining & Knowledge Management (DaKM 2024)

Welcome to DaKM 2024

9^th International Conference on Data Mining & Knowledge Management (DaKM 2024)

September 21-22, 2024, Copenhagen, Denmark

Hybrid--Registered authors can present their work online or face to face ^New

Scope Call for Participation Program Schedule

9^th International Conference on Data Mining & Knowledge Management (DaKM 2024) will provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum.

Registered authors are now able to present their work through our online platforms

Call for Papers

9^th International Conference on Data Mining & Knowledge Management (DaKM 2024) will provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum.

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 include, but are not limited to, the following

Data Mining Foundations
Biometrics
Clustering
Data Mining Applications
Data Streams Mining, Graph Mining
Databases, Bioinformatics
Educational Data Mining
Financial Modeling
Forecasting, Classification
Image Analysis
Multimedia Data Mining, Web Mining
Parallel and Distributed Data Mining Algorithms
Pre-processing Techniques, Visualization
Security and Information Hiding in Data Mining
Social Networks
Spatial Data Mining, Text Video

Knowledge Processing
Consistent Data Model
Consolidating, and Explaining Discovered Knowledge
Data and Knowledge Representation
Exploring Data Analysis, Inference of Causes
Including Pre- and Post-processing
Integrating Constraints and Knowledge in the KDD Process
Integration of Data Warehousing
Interactive Data Exploration/visualization and Discovery
Knowledge Discovery Framework and Process
Languages and Interfaces for Data Mining
Mining from Low-Quality Information Sources
Mining Trends
OLAP and Data Mining
Opportunities and Risks
Prediction, Evaluating
Statistical Techniques for Generation a Robust

Paper Submission

Authors are invited to submit papers through the conference Submission System by Closed . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).