Persuasion and recommendation system applied to a cognitive assistant

  1. COSTA, Angelo 1
  2. HERAS, Stella 2
  3. PALANCA, Javier 2
  4. NOVAIS, Paulo 1
  5. JULIÁN, Vicente 2
  1. 1 Universidade do Minho
    info

    Universidade do Minho

    Braga, Portugal

    ROR https://ror.org/037wpkx04

  2. 2 Universidad Politécnica de Valencia
    info

    Universidad Politécnica de Valencia

    Valencia, España

    ROR https://ror.org/01460j859

Revista:
ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal

ISSN: 2255-2863

Año de publicación: 2016

Volumen: 5

Número: 2

Páginas: 89-99

Tipo: Artículo

DOI: 10.14201/ADCAIJ2016528999 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal

Objetivos de desarrollo sostenible

Resumen

In this paper, we present a persuasive recommendation module included in the iGenda framework. iGenda is a cognitive assistant that helps care-receivers and caregivers in the management of their activities of daily living, by resolving scheduling conflicts and promoting active aging activities. The proposed new module will allow the system to select and recommend to the users an event that potentially best suits to his/her interests (likes or medical condition). The multi-agent approach followed by the iGenda framework facilitates an easy integration of these new features. The social objective is to promote social activities and engaging the users in physical or psychological activities that improve their medical condition.

Referencias bibliográficas

  • Andrade, F., Neves, J., Novais, P., Machado, J., and Abelha, A., 2005. Legal Security and Credibility in Agent Based Virtual Enterprises. In IFIP — The International Federation for Information Processing, pages 503–512. Springer. doi:10.1007/0-387-29360-4_53.
  • Andrade, F., Novais, P., Machado, J., and Neves, J., 2007. Contracting agents: legal personality and representation. Artificial Intelligence and Law, 15(4):357–373. doi:10.1007/s10506-007-9046-0.
  • Berkovsky, S., Kuflik, T., and Ricci, F., 2007. Mediation of user models for enhanced personalization in recommender systems. User Modeling and User-Adapted Interaction, 18(3):245–286. doi:10.1007/ s11257-007-9042-9.
  • Burke, R., 2002. Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction, 12(4):331–370. doi:10.1023/a:1021240730564.
  • Castillo, J. C., Carneiro, D., Serrano-Cuerda, J., Novais, P., Fernández-Caballero, A., and Neves, J., 2013. A multi-modal approach for activity classification and fall detection. International Journal of Systems Science, 45(4):810–824. doi:10.1080/00207721.2013.784372.
  • Chesñevar, C., Maguitman, A. G., and González, M. P., 2009. Empowering Recommendation Technologies Through Argumentation. In Argumentation in Artificial Intelligence, pages 403–422. Springer. doi:10. 1007/978-0-387-98197-0_20.
  • Costa, Â., Castillo, J. C., Novais, P., Fernández-Caballero, A., and Simoes, R., 2012. Sensor-driven agenda for intelligent home care of the elderly. Expert Systems with Applications, 39(15):12192–12204. doi: 10.1016/j.eswa.2012.04.058.
  • Costa, A., Novais, P., Corchado, J. M., and Neves, J., 2011. Increased performance and better patient attendance in an hospital with the use of smart agendas. Logic Journal of IGPL, 20(4):689–698. doi:10.1093/jigpal/ jzr021.
  • Costa, A., Novais, P., and Simoes, R., 2014. A Caregiver Support Platform within the Scope of an Ambient Assisted Living Ecosystem. Sensors, 14(3):5654–5676. doi:10.3390/s140305654. Heras, S., Botti, V., and Julián, V., 2012. Argument-based agreements in agent societies. Neurocomputing, 75(1):156–162. doi:10.1016/j.neucom.2011.02.022.
  • Heras, S., Navarro, M., Botti, V., and Julián, V., 2010. Applying Dialogue Games to Manage Recommendation in Social Networks. In Lecture Notes in Computer Science, pages 256–272. Springer. doi:10.1007/ 978-3-642-12805-9_15.
  • Holzinger, A., Ziefle, M., and Röcker, C., 2010. Human-Computer Interaction and Usability Engineering for Elderly (HCI4AGING): Introduction to the Special Thematic Session. In Lecture Notes in Computer Science, pages 556–559. Springer. doi:10.1007/978-3-642-14100-3_83.
  • Linden, G., Hong, J., Stonebraker, M., and Guzdial, M., 2009. Recommendation algorithms, online privacy, and more. Communications of the ACM, 52(5):10. doi:10.1145/1506409.1506434.
  • Lindley, S. and Wallace, J., 2015. Placing in Age. ACM Transactions on Computer-Human Interaction, 22(4):1– 39. doi:10.1145/2755562.
  • Pazzani, M. J. and Billsus, D., 2007. Content-Based Recommendation Systems. In The Adaptive Web, pages 325–341. Springer. doi:10.1007/978-3-540-72079-9_10. Schafer, J. B., Frankowski, D., Herlocker, J., and Sen, S., 2007. Collaborative Filtering Recommender Systems. In The Adaptive Web, pages 291–324. Springer. doi:10.1007/978-3-540-72079-9_9.