A comparison of general vs personalised affective models for the prediction of topical relevance

SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2010, Pages 371-378

  Arapakis, Ioannis ^a   Athanasakos, Konstantinos ^a   Jose, Joemon M ^a  

^a UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

Experimentation; Human factors; Performance

Indexed keywords

AFFECTIVE MODEL; EXPERIMENTATION; FACIAL EXPRESSION DATA; GENERAL MODEL; HUMAN FACTORS; IMPLICIT FEEDBACK; INDIVIDUAL DIFFERENCES; PERFORMANCE; PERSONALISATION; SEMANTIC GAP;

FEATURE EXTRACTION; HUMAN ENGINEERING; INFORMATION RETRIEVAL; INFORMATION RETRIEVAL SYSTEMS;

EXPERIMENTS;

EID: 77956023044     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1835449.1835512     Document Type: Conference Paper

References (24)

1. E. Agichtein, E. Brill, and S. Dumais. Improving web search ranking by incorporating user behavior information. In Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, pages 19-26, New York, NY, USA, 2006. ACM.
2. E. Agichtein, E. Brill, S. Dumais, and R. Ragno. Learning user interaction models for predicting web search result preferences. In Proceedings of the 29th annual international A CM SIGIR conference on Research and development in information retrieval, pages 3-10, New York, NY, USA, 2006. ACM.
3. I. Arapakis, J. M. Jose, and P. D. Gray. Affective feedback: an investigation into the role of emotions in the information seeking process. In Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pages 395-402, New York, NY, USA, 2008. ACM.
4. I. Arapakis, I. Konstas, and M. Jose, J. Using facial expressions and peripheral physiological signals as implicit indicators of topical relevance. In Proceedings of the seventeen ACM international conference on Multimedia, pages 461-470, NY, USA, 2009. ACM.
5. I. Arapakis, Y. Moshfeghi, H. Joho, R. Ren, D. Hannah, and J. M. Jose. Enriching user profiling with affective features for the improvement of a multimodal recommender system. In Proceeding of the A CM International Conference on Image and Video Retrieval, pages 1-8, NY, USA, 2009. ACM.
6. R. Badi, S. Bae, J. M. Moore, K. Meintanis, A. Zacchi, H. Hsieh, F. Shipman, and C. C. Marshall. Recognizing user interest and document value from reading and organizing activities in document triage. In Proceedings of the 11th international conference on Intelligent user interfaces, pages 218-225, New York, NY, USA, 2006. ACM.
7. N. J. Belkin. Anomalous states of knowledge as a basis for information retrieval. Canadian Journal of Information Science, 5:133-143, 1980.
8. P. Borlund. Experimental components for the evaluation of interactive information retrieval systems. Journal of Documentation, 56(1):71-90, 2000.
9. M. Daoud, L. Tamine-Lechani, and M. Boughanem. Learning user interests for a session-based personalized search. In Proceedings of the second international symposium on Information interaction in context, pages 57-64, New York, NY, USA, 2008. ACM.
10. P. Ekman. Facial Expressions, chapter 16, pages 301-320. The Handbook of Cognition and Emotion. U.K.: John Wiley & Sons, Ltd, 1999.
11. P. Ekman. Emotions Revealed: Recognizing Faces and Feelings to Improve Communication and Emotional Life. Times Books, New York, 2003.
12. T. Joachims, L. Granka, B. Pan, H. Hembrooke, and G. Gay. Accurately interpreting clickthrough data as implicit feedback. In Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, pages 154-161, New York, NY, USA, 2005. ACM.
13. J. Koenemann and N. J. Belkin. A case for interaction: a study of interactive information retrieval behavior and effectiveness. In Proceedings of the SIGCHI conference on Human factors in computing systems, pages 205-212, New York, NY, USA, 1996. ACM.
14. F. Liu, C. Yu, and W. Meng. Personalized web search by mapping user queries to categories. In Proceedings of the eleventh international conference on Information and knowledge management, pages 558-565, New York, NY, USA, 2002. ACM.
15. M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In Proceedings of the 17th annual international A CM SIGIR conference on Research and development in information retrieval, pages 272-281, NY, USA, 1994. Springer-Verlag New York, Inc.
16. D. W. Oard and J. Kim. Modeling information content using observable behavior, 2001.
17. M. Pantic and L. Rothkrantz. Expert system for automatic analysis of facial expression. Image and Vision Computing Journal, 18(11):881-905, August 2000.
18. M. Pantic and L. J. M. Rothkrantz. Toward an affect-sensitive multimodal human-computer interaction. Proceedings of the IEEE, 91(9):1370-1390, Sept. 2003.
19. M. Pantic, N. Sebe, C. J. F., and T. Huang. Affective multimodal human-computer interaction. In Proceedings of the 13th annual ACM international conference on Multimedia, pages 669-676, New York, NY, USA, 2005. ACM.
20. K. Puolamäki, J. Salojärvi, E. Savia, J. Simola, and S. Kaski. 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, New York, NY, USA, 2005. ACM.
21. Y. Rui and T. Huang. Optimizing learning in image retrieval. In IEEE Conference on Computer Vision and Pattern Recognition, volume 1, pages 236-243, 2000.
22. N. Sebe, M. S. Lew, Y. Sun, I. Cohen, T. Gevers, and T. S. Huang. Authentic facial expression analysis. Image Vision Comput., 25(12):1856-1863, 2007.
23. J. Teevan, S. T. Dumais, and E. Horvitz. Personalizing search via automated analysis of interests and activities. In Proceedings of the 28th annual international A CM SIGIR conference on Research and development in information retrieval, pages 449-456, New York, NY, USA, 2005. ACM.
24. R. Valenti, N. Sebe, and T. Gevers. Facial expression recognition: A fully integrated approach. 14th International Conference on Image Analysis and Processing Workshops, pages 125-130, 2007.