On-location / Digital Conference

International Conference on Knowledge Discovery and Machine Learning (ICKDML-27)

07th - 08th Jun 2027,Tianjin, China

In Association With:

Call for Paper


Important Dates


Early Bird Registration

08th May 2027

Paper Submission Deadline

13th May 2027

Registration Deadline

23rd May 2027

Conference Date

07th - 08th Jun 2027

Conference Updates:

"Stay updated with Science Cite Conference news."

  • Early-Bird Registration Reminder:
    Early-bird registration for the Science Cite Conference in Tianjin ends soon! Register Now!
  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in Tianjin conference.
  • Peer Review Process:
    The peer review process will begin soon for Tianjin conference.
  • Networking with Global Experts:
    Join global experts at our conference in Tianjin.
  • Opportunity for Scopus-Indexed Journal Publication:
    Your research could be published in a Scopus-Indexed Journal. Submit Your Abstract
  • SDG-Inspired Conference Focus:
    Present your work aligned with Sustainable Development Goals.

Call For Papers

The ICKDML bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Knowledge Discovery and Machine Learning, encouraging applied research, case studies, and industry-driven innovations.

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

  • Knowledge representation and machine learning
  • Data mining techniques for knowledge discovery
  • Machine learning for pattern recognition
  • Semantic web technologies and AI
  • Knowledge graphs in machine learning applications
  • AI for decision support systems
  • Collaborative knowledge discovery approaches
  • Ethics in knowledge discovery processes
  • Machine learning for information retrieval
  • Interdisciplinary applications of knowledge discovery
  • Real-time knowledge extraction techniques
  • Impact of AI on knowledge management
  • Machine learning for scientific discovery
  • Knowledge-based systems and AI
  • Future trends in knowledge discovery
  • AI for organizational learning and innovation
  • Data-driven decision making in organizations
  • Machine learning for domain-specific knowledge
  • Visualization techniques for knowledge discovery
  • Collaborative platforms for knowledge sharing

Assessment

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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