Bringing Psychological, Affective and Motivational Relevance Frameworks to Real Information Retrieval Systems

Oswald Barral

2015

Abstract

References

  1. Ajanki, A., Hardoon, D. R., Kaski, S., Puolamäki, K., and Shawe-Taylor, J. (2009). Can eyes reveal interest? implicit queries from gaze patterns. User Modeling and User-Adapted Interaction, 19(4):307-339.
  2. Allanson, J. and Wilson, G. M. (2002). Physiological computing. In CHI'02 Extended Abstracts on Human Factors in Computing Systems, pages 912-913. ACM.
  3. Barral, O., Eugster, M. J., Ruotsalo, T., Spapé, M. M., Kosunen, I., Ravaja, N., Kaski, S., and Jacucci, G. (2015). Exploring peripheral physiology as a predictor of perceived relevance in information retrieval. In Proceedings of the 20th International Conference on Intelligent User Interfaces (in Press), IUI 7815, New York, NY, USA. ACM.
  4. Barral, O. and Jacucci, G. (2014). Applying physiological computing methods to study psychological, affective and motivational relevance. In Symbiotic Interaction, Third International Workshop, Symbiotic 2014. Springer.
  5. Barral, O., Kosunen, I., and Jacucci, G. Influence of reading speed on pupil size as a measure of perceived relevance. In Proceedings of the Joint Workshop on Personalized Information Access (PIA 2014), in conjunction with the 22nd conference on User Modeling, Adaptation and Personalization (UMAP 2014).
  6. Barry, C. L. (1994). User-defined relevance criteria: an exploratory study. JASIS, 45(3):149-159.
  7. Borlund, P. (2003). The concept of relevance in ir. Journal of the American Society for information Science and Technology, 54(10):913-925.
  8. Borlund, P. and Ingwersen, P. (1998). Measures of relative relevance and ranked half-life: performance indicators for interactive ir. In Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, pages 324-331. ACM.
  9. Cacioppo, J. T., Tassinary, L. G., Berntson, G. G., et al. (2007). Handbook of psychophysiology, volume 2. Cambridge University Press New York.
  10. Cosijn, E. and Ingwersen, P. (2000). Dimensions of relevance. Information Processing & Management, 36(4):533-550.
  11. Eugster, M. J., Ruotsalo, T., Spapé, M. M., Kosunen, I., Barral, O., Ravaja, N., Jacucci, G., and Kaski, S. (2014). Predicting term-relevance from brain signals. In Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR 7814, pages 425-434, New York, NY, USA. ACM.
  12. Fairclough, S. H. and Gilleade, K. (2014). Advances in Physiological Computing. Springer.
  13. Gevins, A. and Smith, M. E. (2003). Neurophysiological measures of cognitive workload during humancomputer interaction. Theoretical Issues in Ergonomics Science, 4(1-2):113-131.
  14. Harter, S. P. (1992). Psychological relevance and information science. Journal of the American Society for information Science, 43(9):602-615.
  15. Ingwersen, P. (1996). Cognitive perspectives of information retrieval interaction: elements of a cognitive ir theory. Journal of documentation, 52(1):3-50.
  16. Kapoor, A., Burleson, W., and Picard, R. W. (2007). Automatic prediction of frustration. International Journal of Human-Computer Studies, 65(8):724-736.
  17. Loboda, T. D., Brusilovsky, P., and Brunstein, J. (2011). Inferring word relevance from eye-movements of readers. In Proceedings of the 16th international conference on Intelligent user interfaces, pages 175-184. ACM.
  18. Lorist, M. M., Bezdan, E., ten Caat, M., Span, M. M., Roerdink, J. B., and Maurits, N. M. (2009). The influence of mental fatigue and motivation on neural network dynamics; an eeg coherence study. Brain research, 1270:95-106.
  19. Mizzaro, S. (1997). Relevance: The whole history. Journal of the American society for information science, 48(9):810-832.
  20. Mizzaro, S. (1998). How many relevances in information retrieval? Interacting with computers, 10(3):303-320.
  21. Oliveira, F. T., Aula, A., and Russell, D. M. (2009). Discriminating the relevance of web search results with measures of pupil size. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 2209-2212. ACM.
  22. Puolamäki, K., Salojärvi, J., Savia, E., Simola, J., and Kaski, S. (2005). Combining eye movements and collaborative filtering for proactive information retrieval. In Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, pages 146-153. ACM.
  23. Saracevic, T. (1975). Relevance: A review of and a framework for the thinking on the notion in information science. Journal of the American Society for Information Science, 26(6):321-343.
  24. Saracevic, T. (1996). Relevance reconsidered. In Proceedings of the second conference on conceptions of library and information science (CoLIS 2), pages 201- 218. ACM Press.
  25. Saracevic, T. (1997). The stratified model of information retrieval interaction: Extension and applications. In Proceedings of the annual meeting-American Society For Information Science, volume 34, pages 313-327. Learned Information (Europe) LTD.
  26. Saracevic, T. (2007a). Relevance: A review of the literature and a framework for thinking on the notion in information science. part ii: Nature and manifestations of relevance. Journal of the American Society for Information Science and Technology, 58(13):1915-1933.
  27. Saracevic, T. (2007b). Relevance: A review of the literature and a framework for thinking on the notion in information science. part iii: Behavior and effects of relevance. Journal of the American Society for Information Science and Technology, 58(13):2126-2144.
  28. Schamber, L. (1994). Relevance and information behavior. Annual review of information science and technology (ARIST), 29:3-48.
  29. Schutz, A. and Zaner, R. (1970). Reflections on the Problem of Relevance. Greenwood Press.
  30. Sperber, D. and Wilson, D. (1986). Relevance: Communication and Cognition. Harvard University Press, Cambridge, MA, USA.
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Paper Citation


in Harvard Style

Barral O. (2015). Bringing Psychological, Affective and Motivational Relevance Frameworks to Real Information Retrieval Systems . In Doctoral Consortium - DCPhyCS, (PhyCS 2015) ISBN , pages 3-8


in Bibtex Style

@conference{dcphycs15,
author={Oswald Barral},
title={Bringing Psychological, Affective and Motivational Relevance Frameworks to Real Information Retrieval Systems},
booktitle={Doctoral Consortium - DCPhyCS, (PhyCS 2015)},
year={2015},
pages={3-8},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={},
}


in EndNote Style

TY - CONF
JO - Doctoral Consortium - DCPhyCS, (PhyCS 2015)
TI - Bringing Psychological, Affective and Motivational Relevance Frameworks to Real Information Retrieval Systems
SN -
AU - Barral O.
PY - 2015
SP - 3
EP - 8
DO -