Personality-Based Active Learning for Collaborative Filtering Recommender Systems

Elahi, Mehdi; Braunhofer, Matthias; Ricci, Francesco; Tkalčič, Marko

doi:10.1007/978-3-319-03524-6_31

Cited by 81 publications

(65 citation statements)

References 20 publications

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“…Uma vez que os EA podem ser considerados um componente da personalidade de um indivíduo [Klašnja-Milićević et al 2017], é conveniente citar que há estudos com resultados indicando maior eficácia e lealdade dos usuários em sistemas baseados em personalidade do que em sistemas não baseados em personalidade [Hu e Pu 2011 apud Roshchina 2012] [Elahi et al 2013] [Xia et al 2014].…”

Section: Referencial Teóricounclassified

Um Estudo sobre a Influência das Dimensões do Modelo Felder-Silverman na Recomendação de Recursos Educacionais baseada nos Estilos de Aprendizagem dos Alunos

Aguiar¹,

Barbosa²,

Fechine³

et al. 2017

Anais Do XXVIII Simpósio Brasileiro De Informática Na Educação (SBIE 2017)

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Abstract. It is possible to use the theory of Learning Styles to build the user profiles in Recommender Systems for Learning (RSL). This paper presents a study about the influence of the four dimensions of the Felder-Silverman Learning Styles Model (FSLSM) IntroduçãoA busca por melhorias na recomendação personalizada de conteúdo no contexto educacional é pesquisa corrente. Os alunos têm necessidades individuais, sendo importante reconhecer, portanto, que cada um tem sua própria maneira de receber e processar informações, resolver problemas e expor ideias.Identificar os Estilos de Aprendizagem (EA) dos alunos é uma das formas para a obtenção de suas preferências, propiciando materiais de aprendizagem mais efetivos no processo de ensino-aprendizagem [Aguiar, Fechine e Costa 2014] [Valaski, Malucelli e Reinehr 2011]. Os EA se referem aos modos a partir dos quais os indivíduos preferem receber e processar informações. Dentre os modelos existentes, destaca-se o modelo

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Section: Referencial Teóricounclassified

Um Estudo sobre a Influência das Dimensões do Modelo Felder-Silverman na Recomendação de Recursos Educacionais baseada nos Estilos de Aprendizagem dos Alunos

Aguiar¹,

Barbosa²,

Fechine³

et al. 2017

Anais Do XXVIII Simpósio Brasileiro De Informática Na Educação (SBIE 2017)

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“…Elahi et al [23] propose the enrichment of a variety of active learning techniques with personality data. The process of active learning involves the step of gathering preliminary information and the learning phase itself that involves classification of properties and recognition of patterns.…”

Section: Personality-based Recommender Systemsmentioning

confidence: 99%

TWIN: Personality-based Intelligent Recommender System

Roshchina

Cardiff

Rosso

2015

IFS

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Abstract. This paper presents the "Tell me What I Need" (TWIN) Personality-based Intelligent Recommender System, the goal of which is to recommend items chosen by like-minded (or "twin") people with similar personality types which we estimate from their writings. In order to produce recommendations it applies the results achieved in the personality from the text recognition research field to Personality-based Recommender System user profile modelling. In this way it creates a bridge between the efforts of automatic personality score estimation from plain text and the field of Intelligent Recommender Systems. The paper describes the TWIN system architecture, and results of the experimentation with the system in the online travelling domain in order to investigate the possibility of providing valuable recommendations of hotels of the TripAdvisor website for "like-minded people". The results compare favourably with related experiments, although they demonstrate the complexity of this challenging task.

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“…Personality has been gaining popularity in research on personalized services. It has been used to alleviate the coldstart problem in recommender systems [4,15]. Research has been carried out to understand how personality relates to user preferences in multiple domains [1].…”

Section: Related Workmentioning

confidence: 99%

Personality Correlates for Digital Concert Program Notes

Tkalčič

Ferwerda

Hauger

et al. 2015

Lecture Notes in Computer Science

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Abstract. In classical music concerts, the concert program notes are distributed to the audience in order to provide background information on the composer, piece and performer. So far, these have been printed documents composed mostly of text. With some delay, mobile devices are making their way also in the world of classical concerts, hence offering additional options for digital program notes comprising not only text but also images, video and audio. Furthermore, these digital program notes can be personalized. In this paper, we present the results of a user study that relates personal characteristics (personality and background musical knowledge) to preferences for digital program notes.

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Personality-Based Active Learning for Collaborative Filtering Recommender Systems

Cited by 81 publications

References 20 publications

Um Estudo sobre a Influência das Dimensões do Modelo Felder-Silverman na Recomendação de Recursos Educacionais baseada nos Estilos de Aprendizagem dos Alunos

Um Estudo sobre a Influência das Dimensões do Modelo Felder-Silverman na Recomendação de Recursos Educacionais baseada nos Estilos de Aprendizagem dos Alunos

TWIN: Personality-based Intelligent Recommender System

Personality Correlates for Digital Concert Program Notes

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