3rd International Conference on Data Mining and Big Data (DMBD 2020)

  • 24-26 Jul 2020
  • Xiamen, China

Description

The 3rd International Conference on Data Mining and Big Data (DMBD 2020) covers topics such as:

  • Data Mining
    • Web mining
    • Data Streams Mining
    • Spatial Data Mining
    • Graph Mining
    • Pre-processing Techniques
    • Multimedia Data Mining
    • Parallel and Distributed Data mining Algorithms
    • Security and Information Hiding in Data Mining
  • Big Data
    • Big data architectures
    • Big data foundations
    • Applications of Big data
    • Big Data management
    • Big data analytics for prediction
    • Reasoning on Big data
    • Big data and cloud technologies
    • Deep Analytics
    • High performance computing on Big data
    • Big data and Internet of Things
    • Big data quality and provenance, Big data persistence and preservation
    • Scalable access to Big Data
    • Big data transformations, processing and storage
    • Big data protection, integrity, privacy, and pseudonymisation mechanisms
    • Big data software
    • Big data semantics, interoperability, search and mining
    • Big data understanding
    • Big Data visualization and user experience mechanisms
    • Unknown in large Data Graphs

The 3rd International Conference on Data Mining and Big Data (DMBD 2020) will be held in Xiamen, China on 24-26 Jul 2020.

Venue

Xiamen,
China
View Hotels near Venue
Free cancellation available

More Details

Prices:
250-550 US Dollar
Organizer:
IAASE
Website:

Future Events

  • 3rd International Conference on Data Mining and Big Data (DMBD 2020) - 24-26 Jul 2020, Xiamen, China (81605)
  • 4th International Conference on Data Mining and Big Data (DMBD 2021) - Jul 2021 (73358)

Past Events

  • 2nd International Conference on Data Mining and Big Data (DMBD 2019) - 19-21 Jul 2019, Pacific Hotel Seoul, Seoul, Korea (South) (81604)

Important

Please, check the official conference website for possible changes, before you make any traveling arrangements

Prices are for evaluation only.

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