Sports analytics—Evaluation of basketball players and team performance

V Sarlis, C Tjortjis - Information Systems, 2020 - Elsevier
Given the recent trend in Data Science (DS) and Sports Analytics, an opportunity has arisen
for utilizing Machine Learning (ML) and Data Mining (DM) techniques in sports. This paper …

[HTML][HTML] Data mining algorithms for smart cities: A bibliometric analysis

A Kousis, C Tjortjis - Algorithms, 2021 - mdpi.com
Smart cities connect people and places using innovative technologies such as Data Mining
(DM), Machine Learning (ML), big data, and the Internet of Things (IoT). This paper presents …

Social media types: introducing a data driven taxonomy

P Koukaras, C Tjortjis, D Rousidis - Computing, 2020 - Springer
Social Media (SM) have been established as multifunctional networking tools that tend to
offer an increasingly wider variety of services, making it difficult to determine their core …

Unsupervised Learning in NBA Injury Recovery: Advanced Data Mining to Decode Recovery Durations and Economic Impacts

G Papageorgiou, V Sarlis, C Tjortjis - Information, 2024 - mdpi.com
This study utilized advanced data mining and machine learning to examine player injuries in
the National Basketball Association (NBA) from 2000–01 to 2022–23. By analyzing a …

Smart healthcare support using data mining and machine learning

T Chatzinikolaou, E Vogiatzi, A Kousis… - IoT and WSN based Smart …, 2022 - Springer
Ever since the first cities were created, they have been dependent on technology to sustain
life. The smart city paradigm integrates advanced monitoring, sensing, communication, and …

Mining association rules from COVID-19 related twitter data to discover word patterns, topics and inferences

P Koukaras, C Tjortjis, D Rousidis - Information Systems, 2022 - Elsevier
This work utilizes data from Twitter to mine association rules and extract knowledge about
public attitudes regarding worldwide crises. It exploits the COVID-19 pandemic as a use …

Enabling the analysis of personality aspects in recommender systems

S Yakhchi, A Beheshti, SM Ghafari, M Orgun - arxiv preprint arxiv …, 2020 - arxiv.org
Existing Recommender Systems mainly focus on exploiting users' feedback, eg, ratings, and
reviews on common items to detect similar users. Thus, they might fail when there are no …

Learning Complex Users' Preferences for Recommender Systems

S Yakhchi - arxiv preprint arxiv:2107.01529, 2021 - arxiv.org
Recommender systems (RSs) have emerged as very useful tools to help customers with
their decision-making process, find items of their interest, and alleviate the information …

Mining Association Rules from Code (MARC) to support legacy software management

C Tjortjis - Software Quality Journal, 2020 - Springer
This paper presents a methodology for Mining Association Rules from Code (MARC), aiming
at capturing program structure, facilitating system understanding and supporting software …

Mining data to deal with epidemics: case studies to demonstrate real world AI applications

C Nousi, P Belogianni, P Koukaras… - Handbook of Artificial …, 2022 - Springer
The massive growth of Big Data kickstarted a new era for data analytics and knowledge
discovery. Data mining algorithms are employed to analyze different types of data, which …