Program for stream Data Science and Analytics (contributed)

MA-28: Data Science and Analytics - Methodology III
Stream: Data Science and Analytics (contributed)
Room: Virtual Room 28
Chair(s): Maeng Daeju

• Time Series Fault Detection and Diagnosis Using A Two-Stage Attention-Based Recurrent Neural Network in Copper Refining Manufacturing
  Jae-Jin Yoo, Jun-Geol Baek, yunsung Moon, Kyesun Park
• Instance-dependent cost-sensitive learning: Do we really need it?
  Toon Vanderschueren, Bart Baesens, Wouter Verbeke, Tim Verdonck
• Clustering-based representative multivariate time series creation
  Gabor Tamas, Elisabeth Zehendner, David Schmaranzer, Emel Arikan, Gerald Reiner
• Masked-CNN : CNN-based Class Probability Correction using Mask Image
  Maeng Daeju, Jun-Geol Baek

MB-28: Data Science and Analytics - Methodology I
Stream: Data Science and Analytics (contributed)
Room: Virtual Room 28
Chair(s): Cheolsoon Park

• Geometric multidimensional scaling for multidimensional data visualization
  Gintautas Dzemyda, Martynas Sabaliauskas
• Redundancy in big data: towards a trade-off between convergence and performance
  Christian Colot
• A machine learning approach to verify the effectiveness of multi-parameter evolutionary optimization algorithms
  Christos-Georgios Xanthopoulos, Pantelis Lappas, Manolis Kritikos
• Improved Anomaly Scoring for Anomaly Detection Using Auto Encoder based Unsupervised Learning from Unlabeled Data
  Cheolsoon Park, Jun-Geol Baek

MC-28: Data Science and Analytics - Finance, efficiency and security
Stream: Data Science and Analytics (contributed)
Room: Virtual Room 28
Chair(s): Nouri (Nourhan) Sakr

• Investment Efficiency Analysis of European Education and Health Sectors
  Edo Omic, Etleva Gjonca
• Development of a data-driven application to depict the socioeconomic effects of transportation
  Dimitrios Dimitriou, MARIA SARTZETAKI, Aristi Karagkouni
• Methods for reducing the number of alerts about fraudulent transactions in the bank
  Kseniia Ilchenko
• Combinatorial Scheduling for Adaptive Machine Learning in Cybersecurity
  Nouri (Nourhan) Sakr, Cynthia Phillips, Ojas Parekh, Clifford Stein

MD-28: Data Science and Analytics - Applications in Marketing
Stream: Data Science and Analytics (contributed)
Room: Virtual Room 28
Chair(s): Alicia Zanfrillo

• An aspect-based sentiment analysis system to analyze customers’ reviews from food and beverage opinion and review webpages
  Anastasios Liapakis, Theodore Tsiligiridis, Constantine Yialouris, Constantina Kostopoulou
• Analysis of Customer Response Patterns in Direct Marketing Campaigns: A Gibbs Sampling Approach
  Young H. Chun
• Configuration of the glocal responsibility profile with unsupervised learning techniques for value creation
  Alicia Zanfrillo, Rebeca Yuan, Ezequiel Gribaudo, Victoria Leuci, Carola Sosa
• Liner health prediction using intelligent two-stage machine learning models
  Sourav Bhunia, Shoban Babu Balasubramani, Tuhin Kanti Mondal

TB-27: Data Science and Analytics - Applications 1
Stream: Data Science and Analytics (contributed)
Room: Virtual Room 27
Chair(s): Monisha Bhattacharya

• Large-Scale Process Monitoring
  Volker Kraft
• Hourly Temperature Data do not support the Views of the Climate Deniers, Sceptics, and Trivializers: Evidence from Barrow Alaska
  Kevin Forbes
• Minimizing Bias in AI based recommender systems
  Monisha Bhattacharya, Shantanu Biswas, Saikat Chakraborty, Gunjan Bansal

TC-03: Data Science and Analytics - On site session
Stream: Data Science and Analytics (contributed)
Room: Bulding A, Room 3A
Chair(s): Lisa Schetgen

• Does multiple periodicity exist within a trading activity?
  Josip Arneric
• Forecasting the rail freight transport intensity on Corridor X
  Milos Milenkovic, Natasa Milosavljevic, Bojovic Nebojsa, Dejan Lutovac
• Conceptualising the potential of big data analytics to facilitate discrete-event simulation modelling in smart mobility
  Mario Jadric, Maja Cukusic
• Developing a detection and interpretation tool for rumors regarding COVID-19 on Twitter
  Lisa Schetgen, Bram Janssens, Matthias Bogaert

TD-54: Data Science and Analytics - Methodology II
Stream: Data Science and Analytics (contributed)
Room: Virtual Room 54
Chair(s): Annabella Astorino

• Solving the Knapsack Problem Using Reinforcement Learning Techniques
  Samuel Benford, Mohammad Dehghani
• Dynamic L1 Regression
  Botan Citil
• A multi-sphere approach for Multiple Instance Learning classification
  Matteo Avolio, Annabella Astorino, Antonio Fuduli
• Multiple Instance Learning by Polyhedral Approaches
  Annabella Astorino, Matteo Avolio, Antonio Fuduli

WA-27: Data Science and Analytics - Applications in Transportation
Stream: Data Science and Analytics (contributed)
Room: Virtual Room 27
Chair(s): Luigi De Giovanni

• Route based Driving Range Prediction of Electric Vehicles by using Static and Dynamic Data
  Hilal YILMAZ, Betul Yagmahan
• Maintenance Add-on to Logistics: Data fusion for a reduced logistics footprint
  Dino Spirtovic, Rob Brink
• A Deep Imitation Learning Approach for Solving the E-commerce Box-Sizing Problem
  Shanthan Kandula, Srikumar Krishnamoorthy, Debjit Roy
• Mining optimal trajectories for the Air Traffic Flow Management Problem
  Luigi De Giovanni, Martino Echerle, Guglielmo Lulli

WB-27: Data Science and Analytics - Applications 2
Stream: Data Science and Analytics (contributed)
Room: Virtual Room 27
Chair(s): Seunghwan Song

• Contrastive CNN for Mixed-type Pattern Recognition with Single-type Pattern on Wafer Bin Maps
  Yunseon Byun, Jun-Geol Baek
• Multitask learning for data-driven wind farm management and condition-based maintenance
  Angela Meyer
• Prediction of Wet Bulb Globe Temperature using Machine Learning
  CHANG LU, Yeboon Yun, Min Yoon
• Latent Mapping Adversarial Networks in Manufacturing Defect Synthesis
  Seunghwan Song, Jun-Geol Baek