DATA ANALYTICS 2021 - The Tenth International Conference on Data Analytics
October 03, 2021 - October 07, 2021
DATA ANALYTICS 2021: Awards
Onsite and Online Options: In order to accommodate a large number of situations, we are offering the option for either physical presence or virtual participation (pdf slides or pre-recorded videos).
The papers listed below have been selected as "Best Papers" based on the reviews of the original submission, the camera-ready version, and the presentation during the conference. For the awarded papers, a digital award will be issued in the name of the authors. The authors of these papers are also receiving invitations to submit an extended article version to one of the IARIA Journals.
Awarded Papers (also Invited for IARIA Journals)
Feature Engineering and Machine Learning Modelling for Predictive Maintenance Based on Production and Stop Events
Ariel Cedola, Rosaria Rossini, Ilaria Bosi, Davide Conzon
Analyzing the United State’s Nationwide Opioid Crisis and Socio-economic Factors using K-Means Clustering
Ryan McGinnis, Les Sztandera
A Comparison of Machine-Learned Survival Models for Predicting Tenure from Unstructured Résumés
Corné de Ruijt, Vladimer Kobayashi, Sandjai Bhulai
A Concept for a Comprehensive Understanding of Communication in Mobile Forensics
Jian Xi, Michael Spranger, Dirk Labudde
Integrated Architecture of SQL Engine and Data Analytics Tool with Apache Arrow Flight and Its Performance Evaluation
Yuichiro Aoki, Satoru Watanabe
The following papers have been selected on the basis of their contents, specificaly for lending themselves to an interesting extended work. The authors of these papers are receiving invitations to submit an extended article version to one of the IARIA Journals.
Papers Invited for IARIA Journals
Modelling the Consistency between Customer Opinion and Online Rating with VADER Sentiment and Bayesian Networks
Alexandros Bousdekis, Dimitris Kardaras, Stavroula Barbounaki
Discovering DataOps: A Comprehensive Review of Definitions, Use Cases, and Tools
Kiran Mainali, Lisa Ehrlinger, Johannes Himmelbauer, Mihhail Matskin
Detection of Concept Drift in Manufacturing Data with SHAP Values to Improve Error Prediction
Christian Seiffer, Holger Ziekow, Ulf Schreier, Alexander Gerling
Evaluation of Filter Methods for Feature Selection by Using Real Manufacturing Data
Alexander Gerling, Holger Ziekow, Ulf Schreier, Christian Seiffer, Andreas Hess, Djaffar Abdeslam