Integrated Uncertainty in Knowledge Modelling and Decision Making

6th International Symposium, IUKM 2018, Hanoi, Vietnam, March 15-17, 2018, Proceedings

  • Van-Nam Huynh
  • Masahiro Inuiguchi
  • Dang Hung Tran
  • Thierry Denoeux
Conference proceedings IUKM 2018

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10758)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 10758)

Table of contents

  1. Front Matter
    Pages I-XXII
  2. Uncertainty Management and Decision Support

  3. Clustering and Classification

  4. Machine Learning Applications

    1. Front Matter
      Pages 151-151
    2. Thanh Trung Giang, Thanh Phuong Nguyen, Tran Quoc Vinh Nguyen, Dang Hung Tran
      Pages 153-165
    3. Khuong Nguyen-Ngoc, Anh-Cuong Le, Viet-Ha Nguyen
      Pages 166-178
    4. Phuc H. Duong, Hien T. Nguyen, Duy D. Nguyen, Hao T. Do
      Pages 191-202

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 6th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2018, held in Hanoi, Vietnam, in March 2018.
The 39 revised full papers presented in this book were carefully reviewed and selected from 76 initial submissions. The papers are organized in topical sections on uncertainty management and decision support; clustering and classification; machine learning applications; statistical methods; and econometric applications.

Keywords

semantics commerce machine learning stock market esitmation probability stock exchange SVM cluster analysis clustering algorithms question answering classification

Editors and affiliations

  1. 1.Japan Advanced Institute of Science and TechnologyNomiJapan
  2. 2.Osaka UniversityOsakaJapan
  3. 3.Hanoi National University of EducationHanoiVietnam
  4. 4.Université de Technologie de CompiègneCompiègneFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-75429-1
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-75428-4
  • Online ISBN 978-3-319-75429-1
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book
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