Hybrid Conferencee

International Conference on Data Mining and Machine Learning (ICDMM - 26)

17th - 18th July 2026 | Beijing, China
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Conference Brochure
Sample Full Paper
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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Beijing. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Beijing event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Beijing conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Beijing, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Beijing."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICDMM aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Machine Learning, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Data preprocessing techniques for machine learning
02
Supervised vs unsupervised learning methods
03
Data visualization techniques for insights
04
Feature selection methods in data mining
05
Clustering algorithms for big data
06
Anomaly detection in data mining
07
Data mining applications in various domains
08
Predictive modeling techniques in data mining
09
Data mining for social network analysis
10
Text mining techniques and applications
11
Machine learning for data-driven decision making
12
Scalable data mining algorithms
13
Data mining ethics and privacy concerns
14
Real-time data mining applications
15
Integration of big data and machine learning
16
Data mining for healthcare analytics
17
Time series data mining techniques
18
Data mining in finance and economics
19
Challenges in data mining methodologies
20
Future trends in data mining research