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Unimodal regularisation based on beta distribution for deep ordinal regression
(Elsevier, 2022)
Currently, the use of deep learning for solving ordinal classification problems, where categories follow a natural order, has not received much attention. In this paper, we propose an unimodal regularisation based on the ...
Determining the Difficulties of Students With Dyslexia via Virtual Reality and Artificial Intelligence: An Exploratory Analysis
(IEEE, 2022)
Learning disorders are neurological conditions that affect the brain’s ability to interconnect communication areas. Dyslexic students experience problems with reading, memorizing, and exposing concepts; however the magnitude ...
Analysing the Needs of Homeless People Using Feature Selection and Mining Association Rules
(IEEE, 2022)
Homelessness is a social and health problem with great repercussions in Europe. Many non-governmental organisations help homeless people by collecting and analysing large amounts of information about them. However, these ...
Helping university students to choose elective courses by using a hybrid multi-criteria recommendation system with genetic optimization
(Elsevier, 2020)
The wide availability of specific courses together with the flexibility of academic plans in university
studies reveal the importance of Recommendation Systems (RSs) in this area. These systems appear
as tools that help ...
Multi-source and multimodal data fusion for predicting academic performance in blended learning university courses
(Elsevier, 2021)
In this paper we apply data fusion approaches for predicting the final academic performance of university students using multiple-source, multimodal data from blended learning environments. We collect and preprocess data ...
Educational data mining and learning analytics: An updated survey
(Wiley, 2020)
This survey is an updated and improved version of the previous one published
in 2013 in this journal with the title “data mining in education”. It reviews in a
comprehensible and very general way how Educational Data ...
Process mining for self-regulated learning assessment in e-learning
(Springer, 2020)
Content assessment has broadly improved in e-learning scenarios in recent decades. However, the eLearning process can give rise to a spatial and temporal gap that poses interesting challenges for assessment of not only ...
Improving prediction of students’ performance in intelligent tutoring systems using attribute selection and ensembles of different multimodal data sources
(Springer, 2021)
The aim of this study was to predict university students’ learning performance using different sources of performance and multimodal data from an Intelligent Tutoring System. We collected and preprocessed data from 40 ...
A new approach for optimal time-series segmentation
(Elsevier, 2020)
This paper proposes a new optimal approach, called OSTS, to improve the segmentation of time series. The proposed method is based on A* algorithm and it uses an improved version of the well-known Salotti method for obtaining ...
Local-based k values for multi-label k-nearest neighbors rule
(Elsevier, 2022)
Multi-label learning is a growing field in machine learning research. Many applications address instances that simultaneously belong to many categories, which cannot be disregarded if optimal results are desired. Among the ...