WELCOME TO KDMILE

The Symposium on Knowledge Discovery, Mining and Learning (KDMiLe) aims at integrating researchers, practitioners, developers, students and users to present theirs research results, to discuss ideas, and to exchange techniques, tools, and practical experiences – related to the Data Mining and Machine Learning areas. KDMiLe originated from WAAMD (Workshop em Algoritmos e Aplicações de Mineração de Dados) that occurred during five years – 2005 to 2009 – as a Workshop of Brazilian Symposium on Databases (SBBD). Since 2013, KDMiLe is organized alternatively in conjunction with the Brazilian Conference on Intelligent Systems (BRACIS) and the Brazilian Symposium on Databases (SBBD). This year, 2020, in its eighth edition, KDMiLe will be held in Rio Grande on October 20th to 23th in conjunction with the Brazilian Conference on Intelligent Systems (BRACIS). This year KDMiLe is being organized by Universidade Federal do Rio Grande(FURG, Brazil) and Centro de Ciências Computacionais (C3, Brazil). The KDMiLe Program Committee invites submissions containing new ideas and proposals, and also applications, in the Data Mining and Machine Learning areas. Submitted papers will be reviewed based on originality, relevance, technical soundness and clarity of presentation.



GENERAL INFORMATION

This year KDMiLe is being organized by Universidade Federal do Rio Grande(FURG, Brazil) and Centro de Ciências Computacionais (C3, Brazil).. As in the last years, KDMiLe comes with two different tracks: Algorithms and Applications.

  • Applications Track: authors are encouraged to submit papers reporting applications of Machine Learning and Data Mining methods in different areas.
  • Algorithms Track: authors are encouraged to submit papers describing new ideas and concepts in Machine Learning and Data Mining.


  • IMPORTANT DATES
  • Paper submission: July 06th > July 28th >> August 21th, 2020 (firm deadline)
  • Author notification: Until August 13th > September 4th >> September 21th, 2020
  • Camera-ready due: September 2nd > September 19th >> September 28th, 2020


  • SUBMISSION GUIDELINES

    Templates

  • Please download the template for the algorithms track: HERE  Camera ready here
  • Please download the template for the applications track: HERE  Camera ready here  
  • Papers may be written in Portuguese or English, but the  title, the abstract and the keywords must be written in English.
  • Submissions are reviewed following a single blind review process, i.e. you do not need to hide authors' names and affiliations.
  • The manuscript must not exceed 8 pages. Papers exceeding this limit will be automatically rejected without being reviewed by the Program Committee.
  • Papers must be submitted in PDF format. Formats other than PDF will NOT be accepted.
  • Papers must be submitted through the web page: HERE

  • Papers will be published electronically in the KDMiLe proceedings. A preliminary version of the proceedings, including all the accepted papers, will be available to the symposium attendees. Papers submitted to KDMiLe must not have been simultaneously submitted to any other forum (conference or journal), nor should they have already been published elsewhere. The acceptance of a paper implies that at least one of its authors will register for the symposium to present it. Submitted papers will be reviewed based on originality, relevance, technical soundness and clarity of presentation. Please follow the submission template. For further inquiries, please contact the Program Committee Chair at the email: kdmile.symposium@gmail.com.

    Journal Special Issue

    In all past editions, authors of selected papers accepted for presentation in KDMiLe have been invited to submit extended and revised versions of these papers to a special issue of JIDM (Journal of Information and Database Management). This year, we intend to follow this same policy of encouraging the best submissions with publication in an international journal.


    ACCEPTED PAPERS

    HERE



    TOPICS OF INTEREST
      IN DATA MINING (NOT LIMITED TO)
    • Association Rules
    • Classification
    • Clustering
    • Data Mining Applications
    • Data Mining Foundations
    • Evaluation Methodology in Data Mining
    • Feature Selection and Dimensionality Reduction
    • Graph Mining
    • Massive Data Mining
    • Multimedia Data Mining
    • Multirelational Mining
    • Outlier Detection
    • Parallel and Distributed Data Mining
    • Pre and Post Processing
    • Ranking and Preference Mining
    • Privacy and Security in Data Mining
    • Quality and Interest Metrics
    • Sequential Patterns
    • Social Network Mining
    • Stream Data Mining
    • Text Mining
    • Time-Series Analysis
    • Visual Data Mining Web Mining
    • Recommender Systems based on Data Mining
      IN MACHINE LEARNING (NOT LIMITED TO)
    • Active Learning
    • Bayesian Inference
    • Case-Based Reasoning
    • Cognitive Models of Learning
    • Constructive Induction and Theory Revision
    • Cost-Sensitive Learning
    • Deep Learning
    • Ensemble Methods
    • Evaluation Methodology in Machine Learning
    • Fuzzy Learning Systems
    • Inductive Logic Programming and Relational Learning
    • Kernel Methods
    • Knowledge-Intensive Learning
    • Learning Theory
    • Machine Learning Applications
    • Meta-Learning
    • Multi-Agent and Co-Operative Learning
    • Natural Language Processing
    • Probabilistic and Statistical Methods
    • Ranking and Preference Learning
    • Recommender Systems based on Machine Learning
    • Reinforcement Learning
    • Semi-Supervised Learning
    • Supervised Learning
    • Unsupervised Learning
    • Online Learning

    • COMMITTEES
      Steering Committee
      Chair - Luiz Merschmann (UFLA)
      Alexandre Plastino (UFF)
      André Carlos Ponce de Leon Ferreira de Carvalho (ICMC-USP)
      Wagner Meira Jr. (UFMG)
      Ricardo Cerri (UFSCAR)
      Program Chair
      Chair - Elaine Ribeiro de Faria (UFU) - elaine@ufu.br
      Co-Chair - Moacir Antonelli Ponti (ICMC-USP) - moacir@icmc.usp.br
      Local Chair
      Eduardo Nunes Borges (FURG)



      SPONSORS
      PROMOTION
      ORGANIZATION