Affective recommender systems: The role of emotions in recommender systems

CEUR Workshop Proceedings

Volumn 811, Issue , 2011, Pages 9-13

  Tkalčič, Marko ^a   Košir, Andrej ^a   Tasič, Jurij ^a  

^a UNIVERSITY OF LJUBLJANA   (Slovenia)

Author keywords

Emotions; Recommender systems

Indexed keywords

DATA CENTRIC; DESCRIPTORS; EMOTIONS; STAGE MODELS; USER MODELING;

DECISION MAKING;

RECOMMENDER SYSTEMS;

EID: 84891957136     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. G. Adomavicius and Y. Kwon. Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques. IEEE Transactions on Knowledge and Data Engineering, (99):1-1, 2011.
2. G. Adomavicius, R. Sankaranarayanan, S. Sen, and A. Tuzhilin. Incorporating contextual information in recommender systems using a multidimensional approach. ACM Transactions on Information Systems (TOIS), 23(1):103-145, 2005.
3. I. Arapakis, J. Jose, and P. Gray. Affective feedback: An investigation into the role of emotions in the information seeking process. Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, (January):395-402, 2008.
4. 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 syestm. Proceeding of the ACM International Conference on Image and Video Retrieval - CIVR '09, (1):1, 2009.
5. L. Baltrunas. Exploiting contextual information in recommender systems. Proceedings of the 2008 ACM conference on Recommender systems - RecSys '08, page 295, 2008.
6. M. S. Bartlett, G. C. Littlewort, M. G. Frank, C. Lainscsek, I. R. Fasel, and J. R. Movellan. Automatic Recognition of Facial Actions in Spontaneous Expressions. Journal of Multimedia, 1(6):22-35, Sept. 2006.
7. M. Bradley and P. Lang. Measuring emotion: The self-assessment manikin and the semantic differential. Journal of behavior therapy and experimental psychiatry, 25(1):49-59, 1994.
8. C. Creed and R. Beale. Using emotion simulation to influence user attitudes and behavior. HCI workshop at BCS 2005, pages 1-3, 2005.
9. P. Ekman. Facial expression and emotion. American Psychologist, 48(4):384, 1993.
10. P. Ekman. Basic Emotions. In Handbook of Cognition and Emotion, pages 45-60. 1999.
11. A. Hanjalic. Adaptive extraction of highlights from a sport video based on excitement modeling. IEEE Transactions on Multimedia, 7(6):1114-1122, Dec. 2005.
12. J. L. Herlocker, J. A. Konstan, L. Terveen, and J. T. Riedl. Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst, 22(1):5-53, 2004.
13. S. V. Ioannou, A. T. Raouzaiou, V. a. Tzouvaras, T. P. Mailis, K. C. Karpouzis, and S. D. Kollias. Emotion recognition through facial expression analysis based on a neurofuzzy network. Neural networks : The offcial journal of the International Neural Network Society, 18(4):423-35, May 2005.
14. A. Jaimes and N. Sebe. Multimodal human-computer interaction: A survey. Computer Vision and Image Understanding, 108(1-2):116-134, 2007.
15. H. Joho, J. M. Jose, R. Valenti, and N. Sebe. Exploiting facial expressions for affective video summarisation. Proceeding of the ACM International Conference on Image and Video Retrieval - CIVR '09, page 1, 2009.
16. D. Kahneman. A perspective on judgment and choice: mapping bounded rationality. The American psychologist, 58(9):697-720, Sept. 2003.
17. M. Kaminskas and F. Ricci. Location-Adapted Music Recommendation Using Tags. User Modeling, Adaption and Personalization, pages 183-194, 2011.
18. T. Kanade, J. Cohn, and Y. Tian. Comprehensive database for facial expression analysis. In Automatic Face and Gesture Recognition, 2000. Proceedings Fourth IEEE International Conference on, pages 46-53. IEEE, 2000.
19. Y. Koren. Collaborative filtering with temporal dynamics. Communications of the ACM, 53(4):89, Apr. 2010.
20. A. Mehrabian. Pleasure-arousal-dominance: A general framework for describing and measuring individual differences in Temperament. Current Psychology, 14(4):261-292, Dec. 1996.
21. S. Munson, D. X. Zhou, and P. Resnick. Sidelines: An algorithm for increasing diversity in news and opinion aggregators. Proceedings of ICWSM09 Conference on Weblogs and Social Media. San Jose, CA., 2009.
22. M. Pantic and A. Vinciarelli. Implicit human-centered tagging Social Sciences. IEEE Signal Processing Magazine, 26(6):173-180, Nov. 2009.
23. K. Porayska-Pomsta, M. Mavrikis, and H. Pain. Diagnosing and acting on student affect: The tutor's perspective. User Modeling and User-Adapted Interaction: The Journal of Personalization Research, 18(1-2):125-173, 2007.
24. J. Posner, J. a. Russell, and B. S. Peterson. The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology. Development and psychopathology, 17(3):715-34, Jan. 2005.
25. Y. Shi, M. Larson, and A. Hanjalic. Mining mood-specific movie similarity with matrix factorization for context-aware recommendation. Proceedings of the Workshop on Context-Aware Movie Recommendation, pages 34-40, 2010.
26. M. Tkalcic, U. Burnik, and A. Kosir. Using affective parameters in a content-based recommender system for images. User Modeling and User-Adapted Interaction: The Journal of Personalization Research, pages 133-33, Sept. 2010.
27. M. Tkalcic, A. Odic, A. Kosir, and J. Tasic. Comparison of an Emotion Detection Technique on Posed and Spontaneous Datasets. Proceedings of the 19th ERK conference, Portoroz, 2010, 2010.
28. M. Tkalcic, A. Odic, A. Kosir, and J. Tasic. Impact of Implicit and Explicit Affective Labeling on a Recommender System's Performance. Joint Proceedings of the Workshop on Decision Making and Recommendation Acceptance Issues in Recommender Systems (DEMRA 2011) and the 2nd Workshop on User Models for Motivational Systems: The affective and the rational routes to persuasion (UMMS 2011), page 112, 2011.
29. M. Tkalcic, J. Tasic, and A. Kosir. The LDOS-PerAff-1 Corpus of Face Video Clips with Affective and Personality Metadata. Proceedings of Multimodal Corpora: Advances in Capturing, Coding and Analyzing Multimodality (Malta, 2010), LREC, page 111, 2009.
30. G. N. Yannakakis, J. Hallam, and H. H. Lund. Entertainment capture through heart rate activity in physical interactive playgrounds. User Modeling and User-Adapted Interaction, 18(1-2):207-243, Sept. 2008.
31. Z. Zeng, M. Pantic, G. I. Roisman, and T. S. Huang. A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions. IEEE Trans. Pattern Analysis & Machine Intelligence, Vol. 31, No. 1 pp:39-58, 2009.