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    DMML 2021 - 2nd International Conference on Data Mining & Machine Learning (DMML 2021)

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    Website https://necom2021.org/dmml/index | Edit Freely

    Category Statistical Techniques for Generation a Robust;Consistent Data Model; Languages and Interfaces for Data Mining; Mining Trends, Opportunities and Risks.

    Deadline: October 25, 2020 | Date: February 20, 2021-February 21, 2021

    Venue/Country: Dubai, UAE, United Arab Emirates

    Updated: 2020-10-01 21:38:31 (GMT+9)

    Call For Papers - CFP

    February 20~21, 2021, Dubai, UAE

    https://necom2021.org/dmml/index

    Scope

    2nd International Conference on Data Mining & Machine Learning (DMML 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Mining and Machine Learning. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Big Data and Machine Learning.

    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 Data Mining and Machine Learning.

    Topics of Interest

    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

    Machine learning

    Machine Learning Applications

    Learning in knowledge-intensive systems

    Learning Methods and analysis

    Learning Problems

    Deep Learning

    Paper Submission

    Authors are invited to submit papers through the Submission System by October 25, 2020. 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).

    Selected papers from DMML 2021, after further revisions, will be published in the special issue of the following journals

    International Journal of Data Mining & Knowledge Management Process (IJDKP)

    International Journal of Database Management Systems (IJDMS)

    Machine Learning and Applications: An International Journal (MLAIJ)

    International Journal of Web & Semantic Technology (IJWesT)

    Important Dates

    Submission Deadline : October 25, 2020

    Authors Notification : December 25, 2020

    Registration & Camera-Ready Paper Due : January 07, 2021

    Contact Us

    Here’s where you can reach us : dmml@necom2021.org or dmmlconf@yahoo.com


    Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
    Disclaimer: ourGlocal is an open academical resource system, which anyone can edit or update. Usually, journal information updated by us, journal managers or others. So the information is old or wrong now. Specially, impact factor is changing every year. Even it was correct when updated, it may have been changed now. So please go to Thomson Reuters to confirm latest value about Journal impact factor.