Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices

1. Front Matter

   Pages i-xx

   PDF

2. Knowledge Discovery and Pattern Mining

   1. Front Matter

      Pages 1-1

      PDF

   2. Fast Mining of Top-k Frequent Balanced Association Rules

      • Xiangyu Liu, Xinzheng Niu, Jieliang Kuang, Shenghan Yang, Pengpeng Liu

      Pages 3-14

   3. Towards Increasing Open Data Adoption Through Stream Data Integration and Imputation

      • Robert Kunicki, Maciej Grzenda

      Pages 15-27

   4. Towards Efficient Discovery of Periodic-Frequent Patterns in Columnar Temporal Databases

      • Ravikumar Penugonda, Likhitha Palla, Uday Kiran Rage, Yutaka Watanobe, Koji Zettsu

      Pages 28-40

   5. Data-Driven Simulation of Ride-Hailing Services Using Imitation and Reinforcement Learning

      • Haritha Jayasinghe, Tarindu Jayatilaka, Ravin Gunawardena, Uthayasanker Thayasivam

      Pages 41-52

   6. Discovering Spatial High Utility Itemsets in High-Dimensional Spatiotemporal Databases

      • Sai Chithra Bommisetty, Ravikumar Penugonda, Uday Kiran Rage, Minh Son Dao, Koji Zettsu

      Pages 53-65

   7. A Single-Stage Tree-Structure-Based Approach to Determine Fuzzy Average-Utility Itemsets

      • Tzung-Pei Hong, Meng-Ping Ku, Hsiu-Wei Chiu, Wei-Ming Huang, Shu-Min Li, Jerry Chun-Wei Lin

      Pages 66-72

   8. Mining Episode Rules from Event Sequences Under Non-overlapping Frequency

      • Oualid Ouarem, Farid Nouioua, Philippe Fournier-Viger

      Pages 73-85

   9. Distributed Mining of High Utility Time Interval Sequential Patterns with Multiple Minimum Utility Thresholds

      • Sumalatha Saleti, Jaya Lakshmi Tangirala, Ragunathan Thirumalaisamy

      Pages 86-97

3. Artificial Intelligence and Machine Learning

   1. Front Matter

      Pages 99-99

      PDF

   2. Emergency Analysis: Multitask Learning with Deep Convolutional Neural Networks for Fire Emergency Scene Parsing

      • Jivitesh Sharma, Ole-Christoffer Granmo, Morten Goodwin

      Pages 101-112

   3. Comparison of Consolidation Methods for Predictive Learning of Time Series

      • Ryoichi Nakajo, Tetsuya Ogata

      Pages 113-120

   4. Evolutionary Optimization of Convolutional Neural Network Architecture Design for Thoracic X-Ray Image Classification

      • Hassen Louati, Slim Bechikh, Ali Louati, Abdulaziz Aldaej, Lamjed Ben Said

      Pages 121-132

   5. Understanding the Effects of Mitigation on De-identified Data

      • Andrew Chester, Yun Sing Koh, Junjae Lee

      Pages 133-144

   6. Combining Siamese Network and Correlation Filter for Complementary Object Tracking

      • Kosuke Honda, Hamido Fujita

      Pages 145-157

   7. Closed-Form Expressions for Global and Local Interpretation of Tsetlin Machines

      • Christian D. Blakely, Ole-Christoffer Granmo

      Pages 158-172

   8. Explainable Reinforcement Learning with the Tsetlin Machine

      • Saeed Rahimi Gorji, Ole-Christoffer Granmo, Marco Wiering

      Pages 173-187

4. Sematic, Topology, and Ontology Models

   1. Front Matter

      Pages 189-189

      PDF

   2. Semantic Technologies Towards Missing Values Imputation

      • Iker Esnaola-Gonzalez, Unai Garciarena, Jesús Bermúdez

      Pages 191-196

This two-volume set of LNAI 12798 and 12799 constitutes the thoroughly refereed proceedings of the 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, held virtually and in Kuala Lumpur, Malaysia, in July 2021.

The 87 full papers and 19 short papers presented were carefully reviewed and selected from 145 submissions. The IEA/AIE 2021 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include the following:

Part I, Artificial Intelligence Practices: Knowledge discovery and pattern mining; artificial intelligence and machine learning; sematic, topology, and ontology models; medical and health-related applications; graphic and social network analysis; signal and bioinformatics processing; evolutionary computation; attack security; natural language and text processing; fuzzy inference and theory; and sensor and communication networks

Part II, From Theory to Practice: Prediction and recommendation; data management, clustering and classification; robotics; knowledge based and decision support systems; multimedia applications; innovative applications of intelligent systems; CPS and industrial applications; defect, anomaly and intrusion detection; financial and supply chain applications; Bayesian networks; BigData and time series processing; and information retrieval and relation extraction

• artificial intelligence
• classification
• computational linguistics
• correlation analysis
• data mining
• databases
• information retrieval
• internet
• machine learning
• natural language processing
• neural networks
• nlp
• robotics
• semantics
• signal processing
• World Wide Web

• i-SOMET Incorporate Association, Morioka, Japan

  Hamido Fujita

• Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

  Ali Selamat

• Western Norway University of Applied Sciences, Bergen, Norway

  Jerry Chun-Wei Lin

• Texas State University San Marcos, San Marcos, USA

  Moonis Ali

Policies and ethics