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Educational data mining to predict students' academic performance: A survey study
Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …
education and informatics. It has become an imperative research area due to many …
[HTML][HTML] Infrastructure elements for smart campuses: A bibliometric analysis
Sustainable development can be attained at a microlevel and having smart campuses
around the world presents an opportunity to achieve city-wide smartness. In the process of …
around the world presents an opportunity to achieve city-wide smartness. In the process of …
Modeling inter-station relationships with attentive temporal graph convolutional network for air quality prediction
Air pollution is an important environmental issue of increasing concern, which impacts
human health. Accurate air quality prediction is crucial for avoiding people suffering from …
human health. Accurate air quality prediction is crucial for avoiding people suffering from …
Identifying Student Behavior in Smart Classrooms: A Systematic Literature Map** and Taxonomies
The integration of the Internet of Things (IoT) and Artificial Intelligence (AI) in educational
settings has revolutionized the traditional teaching-learning environment, giving rise to the …
settings has revolutionized the traditional teaching-learning environment, giving rise to the …
Jointly modeling spatio–temporal dependencies and daily flow correlations for crowd flow prediction
Crowd flow prediction is a vital problem for an intelligent transportation system construction
in a smart city. It plays a crucial role in traffic management and behavioral analysis, thus it …
in a smart city. It plays a crucial role in traffic management and behavioral analysis, thus it …
Enhancing user interest modeling with knowledge-enriched itemsets for sequential recommendation
Sequential recommendation which aims to predict a user's next interaction based on his/her
previous behaviors, has attracted great attention. Recent studies mainly employ deep …
previous behaviors, has attracted great attention. Recent studies mainly employ deep …
Exploiting explicit item–item correlations from knowledge graphs for enhanced sequential recommendation
In recent years, the research of employing knowledge graphs (KGs) in sequential
recommendation (SR) has received a lot of attention, since the side information extracted …
recommendation (SR) has received a lot of attention, since the side information extracted …
Incorporating heterogeneous user behaviors and social influences for predictive analysis
Behavior prediction based on historical behavioral data have practical real-world
significance. It has been applied in recommendation, predicting academic performance, etc …
significance. It has been applied in recommendation, predicting academic performance, etc …
Multifaceted Relation-aware Meta-learning with Dual Customization for User Cold-start Recommendation
User cold-start scenarios pose great challenges to recommendation systems in accurately
capturing user preferences with sparse interaction records. Besides incorporating auxiliary …
capturing user preferences with sparse interaction records. Besides incorporating auxiliary …
[PDF][PDF] Prediction of On-time Student Graduation with Deep Learning Method.
Universities have an important role in providing quality education to their students so they
can build a foundation for their future. However, a problem that often arises is that the …
can build a foundation for their future. However, a problem that often arises is that the …