Heath-PRIOR: An Intelligent Ensemble Architecture to Identify Risk Cases in Healthcare

Neves, Felipe; Campos, Fernanda; Ströele, Victor; Capretz, Miriam A. M.; Jennings, Morgan; Bryant, Dianne; Dantas, Mário A. R.

doi:10.1109/access.2020.3042342

Cited by 6 publications

(2 citation statements)

References 47 publications

(86 reference statements)

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“…In this component, ontology is used with its rules and knowledge representation. Machine learning techniques are used to create a predictive model [19], where it is possible to recognize the right moment to intervene with recommendations to enrich the student's learning moment.…”

Section: Caers -Conversational Agent In An Educational Recommender Sy...mentioning

confidence: 99%

CAERS: A Conversational Agent for Intervention in MOOCs’ Learning Processes

Rossi

Ströele

Braga

et al. 2021

Lecture Notes in Networks and Systems

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Drets d'ús i reutilitzacióAquesta versió del manuscrit es fa disponible amb una llicència Creative Commons del tipus Atribució No Comercial No Derivades (CC BY-NC-ND) http://creativecommons.org/licenses/by-nc-nd/4.0, que permet baixar-la i compartir-la sempre que se'n citi l'autoria, però sense modificar-la ni utilitzar-la amb finalitats comercials. ConsultesSi creieu que aquest document infringeix els drets d'autor, contacteu amb l'equip de recerca:

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Section: Caers -Conversational Agent In An Educational Recommender Sy...mentioning

confidence: 99%

CAERS: A Conversational Agent for Intervention in MOOCs’ Learning Processes

Rossi

Ströele

Braga

et al. 2021

Lecture Notes in Networks and Systems

Self Cite

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“…Our proposal as in [Bóbó et al 2019] will act in Virtual Learning Environments. A recommendation system, as proposed by [Harrathi et al 2017], and also demonstrated in our group's previous works [Neves et al 2020] [Bóbó et al 2019, will be a component of CAERS project. Different from [Brigui-Chtioui et al 2017] CAERS conversational agent is not recommending learning resources at this moment.…”

Section: Related Workmentioning

confidence: 99%

Identifying pedagogical intervention in MOOCs learning processes: a conversational agent proposal

Rossi

Ströele

Campos

et al. 2021

Anais Do XXXII Simpósio Brasileiro De Informática Na Educação (SBIE 2021)

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Monitoring students in virtual learning environments can be a time-consuming task. Professors and tutors must accompany students in an agile manner. During the COVID-19 pandemic, the use of discussion forums posed new challenges. This work proposes a conversational agent to automatically detect which pedagogical intervention is necessary to guide students in MOOCs environments. Through the attributes of the students' post messages, it is possible to classify which action will be carried out by the agent, applying specific dialogue patterns. In some more specific cases, the tutor's attention is immediately requested. The proposal was evaluated through a feasibility study to verify if semantic detection can contribute to guide the intervention process. According to the results, it is possible to support the tutor, as only 35.2% of interactions required the tutor's action.

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Survey on the Objectives of Recommender Systems: Measures, Solutions, Evaluation Methodology, and New Perspectives

2022

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Recently, recommender systems have played an increasingly important role in a wide variety of commercial applications to help users find favourite products. Research in the recommender system field has traditionally focused on the accuracy of predictions and the relevance of recommendations. However, other recommendation quality measures may have a significant impact on the overall performance of a recommender system and the satisfaction of users. Hence, researchers’ attention in this field has recently shifted to include other recommender system objectives. This article aims to provide a comprehensive review of recent research efforts on recommender systems based on the objectives achieved: relevance, diversity, novelty, coverage, and serendipity. In addition, the definitions and measures associated with these objectives are reviewed. Furthermore, the article surveys the evaluation methodology used to measure the impact of the main challenges on performance and the new applications of the recommender system. Finally, new perspectives, open issues, and future directions are provided to develop the field.

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Heath-PRIOR: An Intelligent Ensemble Architecture to Identify Risk Cases in Healthcare

Cited by 6 publications

References 47 publications

CAERS: A Conversational Agent for Intervention in MOOCs’ Learning Processes

CAERS: A Conversational Agent for Intervention in MOOCs’ Learning Processes

Identifying pedagogical intervention in MOOCs learning processes: a conversational agent proposal

Survey on the Objectives of Recommender Systems: Measures, Solutions, Evaluation Methodology, and New Perspectives

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