International Conference on Data Mining & Knowledge Management (DaKM) 2021
Event submitted on Monday, October 12th 2020, approved by Henry Dalzel ✓

122 Days Until The Event
May 29th, 2021
- May 30th, 2021
Canada
» Vancouver
Event Website
This event has been tagged as follows:
Our Review
This event is happening in Vancouver, Canada on May 29th. Data Mining & Knowledge Management (DaKM 2021) provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum. Topics include data mining foundations, applications and knowledge processing.
- Review written by Henry Dalziel on Monday, October 12th 2020.
- If you would like to edit or ammend facts in my review please either send us a message or connect with me via LinkedIn.
Conference Event Summary
The following description was either submitted by the Conference Organizer on Monday, October 12th 2020, or created by us.
6th International Conference on Data Mining & Knowledge Management (DaKM 2021) 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 these topics only
Topics of interest include, but are not limited to, the following
-Data Mining Foundations
-Parallel and Distributed Data Mining Algorithms
-Data Streams Mining, Graph Mining
-Spatial Data Mining, Text Video
-Multimedia Data Mining, Web Mining
-Pre-processing Techniques, Visualization
-Security and Information Hiding in Data Mining
-Data Mining Applications
-Databases, Bioinformatics
-Biometrics
-Image Analysis
-Financial Modeling
-Forecasting, Classification
-Clustering
-Social Networks
Educational Data Mining
Knowledge Processing
-Data and Knowledge Representation
-Knowledge Discovery Framework and Process
-Including Pre- and Post-processing
-Integration of Data Warehousing
-OLAP and Data Mining
-Integrating Constraints and Knowledge in the KDD Process
-Exploring Data Analysis, Inference of Causes
-Prediction, Evaluating
-Consolidating, and Explaining Discovered Knowledge
-Statistical Techniques for Generation a Robust
-Consistent Data Model
-Interactive Data Exploration/visualization and Discovery
-Languages and Interfaces for Data Mining
-Mining Trends
-Opportunities and Risks
-Mining from Low-Quality Information Sources