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Intelligent Information and Database Systems

14th Asian Conference, ACIIDS 2022, Ho Chi Minh City, Vietnam, November 28–30, 2022, Proceedings, Part II

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Ngoc Thanh Nguyen

    1. Wrocław University of Science and Technology, Wrocław, Poland

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  2. Tien Khoa Tran

    1. Vietnam National University, Ho Chi Minh City, Ho Chi Minh City, Vietnam

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  3. Ualsher Tukayev

    1. Al-Farabi Kazakh National University, Almaty, Kazakhstan

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  4. Tzung-Pei Hong

    1. National University of Kaohsiung, Kaohsiung, Taiwan

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  5. Bogdan Trawiński

    1. Wrocław University of Science and Technology, Wrocław, Poland

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  6. Edward Szczerbicki

    1. University of Newcastle, Newcastle, Australia

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13758)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ACIIDS 2022.

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About this book

This book constitutes the refereed proceedings of the 14th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2022, held Ho Chi Minh City, Vietnam in November 2022.

The 113 full papers accepted for publication in these proceedings were carefully reviewed and selected from 406 submissions. The papers of the 2 volume-set are organized in the following topical sections: data mining and machine learning methods, advanced data mining techniques and applications, intelligent and contextual systems, natural language processing, network systems and applications, computational imaging and vision, decision support and control systems, and data modeling and processing for industry 4.0. The accepted and presented papers focus on new trends and challenges facing the intelligent information and database systems community.

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Keywords

Table of contents (57 papers)

  1. Front Matter

    Pages i-xxxiv
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  2. Machine Learning and Data Mining

    1. Front Matter

      Pages 1-1
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    2. Machine Learning or Lexicon Based Sentiment Analysis Techniques on Social Media Posts

      • David L. John, Bela Stantic
      Pages 3-12

    3. A Comparative Study of Classification and Clustering Methods from Text of Books

      • Barbara Probierz, Jan Kozak, Anita Hrabia
      Pages 13-25

    4. A Lightweight and Efficient GA-Based Model-Agnostic Feature Selection Scheme for Time Series Forecasting

      • Minh Hieu Nguyen, Viet Huy Nguyen, Thanh Trung Huynh, Thanh Hung Nguyen, Quoc Viet Hung Nguyen, Phi Le Nguyen
      Pages 26-39

    5. Machine Learning Approach to Predict Metastasis in Lung Cancer Based on Radiomic Features

      • Krzysztof Fujarewicz, Agata Wilk, Damian Borys, Andrea d’Amico, Rafał Suwiński, Andrzej Świerniak
      Pages 40-50

    6. Covariance Controlled Bayesian Rose Trees

      • Damian Pęszor, Eryka Probierz
      Pages 51-63

    7. Potential of Radiomics Features for Predicting Time to Metastasis in NSCLC

      • Agata Wilk, Damian Borys, Krzysztof Fujarewicz, Andrea d’Amico, Rafał Suwiński, Andrzej Świerniak
      Pages 64-76

    8. A Survey of Network Features for Machine Learning Algorithms to Detect Network Attacks

      • Joveria Rubab, Hammad Afzal, Waleed Bin Shahid
      Pages 77-88

    9. The Quality of Clustering Data Containing Outliers

      • Agnieszka Nowak-Brzezińska, Igor Gaibei
      Pages 89-102

    10. Aggregated Performance Measures for Multi-class Classification

      • Damian Pȩszor, Konrad Wojciechowski
      Pages 103-115

    11. Prediction of Lung Cancer Survival Based on Multiomic Data

      • Roman Jaksik, Jarosław Śmieja
      Pages 116-127

    12. Graph Neural Networks-Based Multilabel Classification of Citation Network

      • Guillaume Lachaud, Patricia Conde-Cespedes, Maria Trocan
      Pages 128-140

    13. Towards Efficient Discovery of Partial Periodic Patterns in Columnar Temporal Databases

      • Penugonda Ravikumar, Venus Vikranth Raj, Palla Likhitha, Rage Uday Kiran, Yutaka Watanobe, Sadanori Ito et al.
      Pages 141-154

    14. Avoiding Time Series Prediction Disbelief with Ensemble Classifiers in Multi-class Problem Spaces

      • Maciej Huk
      Pages 155-166

    15. Speeding Up Recommender Systems Using Association Rules

      • Eyad Kannout, Hung Son Nguyen, Marek Grzegorowski
      Pages 167-179

    16. An Empirical Experiment on Feature Extractions Based for Speech Emotion Recognition

      • Binh Van Duong, Chien Nhu Ha, Trung T. Nguyen, Phuc Nguyen, Trong-Hop Do
      Pages 180-191

    17. Parameter Distribution Ensemble Learning for Sudden Concept Drift Detection

      • Khanh-Tung Nguyen, Trung Tran, Anh-Duc Nguyen, Xuan-Hieu Phan, Quang-Thuy Ha
      Pages 192-203

    18. MLP-Mixer Approach for Corn Leaf Diseases Classification

      • Li-Hua Li, Radius Tanone
      Pages 204-215

    19. A Novel Neural Network Training Method for Autonomous Driving Using Semi-Pseudo-Labels and 3D Data Augmentations

      • Tamás Matuszka, Dániel Kozma
      Pages 216-229
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Other volumes

  1. Intelligent Information and Database Systems

  2. Intelligent Information and Database Systems

  3. Recent Challenges in Intelligent Information and Database Systems

Editors and Affiliations

  • Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen, Bogdan Trawiński

  • Vietnam National University, Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Tien Khoa Tran

  • Al-Farabi Kazakh National University, Almaty, Kazakhstan

    Ualsher Tukayev

  • National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  • University of Newcastle, Newcastle, Australia

    Edward Szczerbicki

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