A Group Recommendation System for Movies based on MAS

Villavicencio, Christian; Schiaffino, Silvia; Díaz-Pace, J. Andrés; Monteserin, Ariel

doi:10.14201/adcaij201653112

Cited by 7 publications

(3 citation statements)

References 13 publications

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“…The emergence of the Social computing paradigm enhanced collaboration between humans and machines, solving social problems by using innovative sociotechnical tools [ 26 ]. Virtual organizations (VOs) of agents are postulated to be one of the most powerful tools for their support [ 58 ]. Some of the functionalities that make them a strong candidate, are their ability to control agent behaviours by the inclusion of normative regulations, their dynamism when forming agent groups and when managing the entry and exit of components, and their ability to describe functional behaviours and structural compositions [ 59 ].…”

Section: Related Workmentioning

confidence: 99%

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A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring

García

Prieto

Alonso

et al. 2017

Sensors

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Real-time Localization Systems have been postulated as one of the most appropriated technologies for the development of applications that provide customized services. These systems provide us with the ability to locate and trace users and, among other features, they help identify behavioural patterns and habits. Moreover, the implementation of policies that will foster energy saving in homes is a complex task that involves the use of this type of systems. Although there are multiple proposals in this area, the implementation of frameworks that combine technologies and use Social Computing to influence user behaviour have not yet reached any significant savings in terms of energy. In this work, the CAFCLA framework (Context-Aware Framework for Collaborative Learning Applications) is used to develop a recommendation system for home users. The proposed system integrates a Real-Time Localization System and Wireless Sensor Networks, making it possible to develop applications that work under the umbrella of Social Computing. The implementation of an experimental use case aided efficient energy use, achieving savings of 17%. Moreover, the conducted case study pointed to the possibility of attaining good energy consumption habits in the long term. This can be done thanks to the system’s real time and historical localization, tracking and contextual data, based on which customized recommendations are generated.

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Section: Related Workmentioning

confidence: 99%

“…The application of Social Computing techniques leads to the creation of Social Machines, entities that are managed by both technical and social practices. Examples of such entities are the Twitter dynamics prediction system, which uses behavioural data [ 58 ], or the Amazon recommendation system [ 60 ].…”

Section: Related Workmentioning

confidence: 99%

A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring

García

Prieto

Alonso

et al. 2017

Sensors

View full text Add to dashboard Cite

show abstract

“…Sin embargo, ninguno de los ejemplos encontrados en la literatura recae en una de las tecnologías con mayor potencial dentro de la Computación Social de entre las mostradas en la Figura 2.2, como son las Organizaciones Virtuales de agentes (Villavicencio et al, 2016). Las Organizaciones Virtuales son sistemas abiertos en los que entidades heterogéneas se agrupan y colaboran para resolver un determinado problema.…”

Section: Computación Social -Social Computingunclassified

Técnicas de computación social e información contextual para el desarrollo de actividades de aprendizaje colaborativo

García¹

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Hay tantas personas a las que agradecer su ayuda y apoyo para que este trabajo llegase a buen puerto, que sería difícil incluirlas a todas en estas líneas. En primer lugar, a mis directores: Javier Prieto y Juan Manuel Corchado, por su trabajo, dedicación y paciencia. Por otro lado, a mis compañeros de Nebusens: Fabio, Richi, Cata y Dante, los cuales tienen gran culpa de este trabajo, así como a Mr L A T E X Martín del Campo. Siempre, a mi familia: Bene, Tina, María y David. Siempre están ahí, siempre confían en mi y nunca permiten una rendición. Por supuesto, a Raquel: porque sabes que lo eres todo para mi, porque nada tiene sentido sin ti, porque constituyes los cimientos de mi vida. Y finalmente, de forma muy especial, a Alejandro y Bernarda: porque de ellos aprendí los valores del trabajo, la honradez y la bondad, porque siempre confiaron en mi y porque, allí donde estén, estarán disfrutando de este momento.

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RETRACTED CHAPTER: New Approach to Recommend Banking Products Through a Hybrid Recommender System

Nieves

2021

Advances in Intelligent Systems and Computing

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A Group Recommendation System for Movies based on MAS

Cited by 7 publications

References 13 publications

A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring

A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring

Técnicas de computación social e información contextual para el desarrollo de actividades de aprendizaje colaborativo

RETRACTED CHAPTER: New Approach to Recommend Banking Products Through a Hybrid Recommender System

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