Article published In:
Interaction Studies
Vol. 16:2 (2015) ► pp.303339
References
Abrazhevich, D., Markopoulos, P., & Rauterberg, M
(2009) Designing internet-based payment systems: Guidelines and empirical basis. Human-Computer Interaction, 24(4), 408–443. DOI logoGoogle Scholar
Atluri, M
(2008) Does music affect blood pressure and heart rate? Project Number J1103, California State Science Fair.Google Scholar
Baltrunas, L., Kaminskas, M., Ludwig, B., Moling, O., Ricci, F., Aydin, A., Lke, K.-H., & Schwaiger, R
(2011) Incarmusic: Context-aware music recommendations in a car. In E-Commerce and web technologies, (pp. 89–100). Springer. DOI logoGoogle Scholar
Bartenwerfer, H
(1969) Einige praktische konsequenzen der aktivierungstheorie. Zeitschrift fur experimentelle und angewandte Psychologie, 161, 195–222.Google Scholar
Bartneck, C., & Hu, J
(2005) Presence in a distributed media environment. In L. Terrenghi, I. Lindt, A. Butz, & M. Kuniavsky (eds.), User experience design for pervasive computing, pervasive 2005, München, Munich, Germany: Ludwig-Maximilians-Universitat. Retrived on October 27, 2014. from http://www.fluidum.org/events/experience05/cameraready/bartneck.pdfGoogle Scholar
Basilico, J., & Hofmann, T
(2004) Unifying collaborative and content-based filtering. In 21st International conference on Machine learning (ICML) , 65–72. ACM. DOI logo
Bernardi, L., Porta, C., & Sleight, P
(2006) Cardiovascular, cerebrovascular, and respiratory changes induced by different types of music in musicians and non-musicians: The importance of silence. Heart, 92(4), 445–452. DOI logoGoogle Scholar
Cano, P., Koppenberger, M., & Wack, N (2005) Content-based music audio recommendation. In 13th Annual ACM International Conference on Multimedia (MULTIMEDIA ‘05) , ­211–212. New York, USA: ACM. DOI logo
Çataltepe, Z., & Altinel, B
(2007) Hybrid music recommendation based on different dimensions of audio content and an entropy measure. In 15th European Signal Processing Conference (EU-SIPCO) , 936–940.
Chai, W., & Vercoe, B
(2000) Using user models in music information retrieval systems. In 1st Annual International Symposium on Music Information Retrieval (ISMIR 2000) , Retrieved on October 27, 2014, from http://ciir.cs.umass.edu/music2000/posters/chai.pdf
Collins, S., Karasek, R., & Costas, K
(2005) Job strain and autonomic indices of cardiovascular disease risk. American Journal of Industrial Medicine, 48(3): 182–193. DOI logoGoogle Scholar
Dumur, E., Barnard, Y., & Boy, G
(2004) Designing for comfort. Human Factors in Design, 111–127.Google Scholar
Elahi, M., Ricci, F., & Rubens, N
(2013) Active learning strategies for rating elicitation in collaborative filtering: A system-wide perspective. ACM Transactions on Intelligent Systems and Technology (TIST), 5(1), 13. DOI logoGoogle Scholar
Elsenbruch, S., Harnish, M., & Orr, W
(1999) Heart rate variability during waking and sleep in healthy males and females. Sleep, 22(8): 1067–1071. DOI logoGoogle Scholar
Elwess, L., & Vogt, F
(2005) Heart rate and stress in a college setting. Bioscience, 31(4), 20–23.Google Scholar
Golbandi, N., Koren, Y., & Lempel, R
(2011) Adaptive bootstrapping of recommender systems using decision trees. In Proceedings of the Fourth ACM International Conference on Web Search and Data Mining , 595–604. ACM. DOI logo
Haas, M., Rijsdam, J., Thomee, B., & Lew, M
(2004) Relevance feedback: Perceptual learning and retrieval in bio-computing, photos, and video. In MIR ‘04: Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information Retrieval , 151–156, New York, NY, USA, ACM. DOI logo
Hoi, S., Lyu, M., & Jin, R
(2006) A unified log-based relevance feedback scheme for image retrieval. IEEE Transactions on Knowledge and Data Engineering, 18(4), 509–524. DOI logoGoogle Scholar
Hu, J
(2006) Design of a distributed architecture for enriching media experience in home theaters. Phd thesis, Department of Industrial Design, Eindhoven University of Technology.Google Scholar
Hu, J., & Bartneck, C
(2008) Culture matters – a study on presence in an interactive movie. CyberPsychology and Behavior, 11(5), 529–535. DOI logoGoogle Scholar
Iwanaga, M
(1995) Relationship between heart rate and preference for tempo of music. Perceptual and Motor Skills, 81(2), 435–440. DOI logoGoogle Scholar
Kaminskas, M., & Ricci, F
(2012) Contextual music information retrieval and recommendation: State of the art and challenges. Computer Science Review, 6(2), 89–119. DOI logoGoogle Scholar
Karjalainen, M
(1985) A new auditory model for the evaluation of sound quality of audio systems. In Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP’85 , vol. 101, 608–611. IEEE. DOI logo
Knees, P., Pohle, T., Schedl, M., & Widmer, G
(2006) Combining audio-based similarity with web-based data to accelerate automatic music playlist generation. In Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval , 147–154. ACM. DOI logo
Knight, W., & Rickard, N (2001) Relaxing music prevents stress-induced increases in subjective anxiety, systolic blood pressure, and heart rate in healthy males and females. Journal of Music Therapy, 38(4), 254–272. DOI logoGoogle Scholar
Koenemann, J
(1996) Supporting interactive information retrieval through relevance feedback. In CHI ‘96: Conference Companion on Human Factors in Computing Systems , 49–50, New York, NY, USA. ACM. DOI logo
Kunz, M.G
(2008) Zombie Notes Bradycardia – Heart Blocks. Dickson Keanaghan, LLC.
Liu, H
(2010) Biosignal controlled recommendation in entertainment systems. Phd thesis, Department of Industrial Design, Eindhoven University of Technology.Google Scholar
Liu, H., Hu, J., & Rauterberg, M
(2008) Airsf: A new entertainment adaptive framework for stress free air travels. In Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology , 183–186. ACM. DOI logo
(2009a) Bio-feedback based in-flight music system design to promote heart health. In International Conference on Machine Learning and Cybernetics (ICMLC) , 446–450. Baoding, China. Citeseer.
(2009b) Music playlist recommendation based on user heartbeat and music preference. In International Conference on Computer Technology and Development (ICCTD’09) , vol. 11, 545–549. IEEE. DOI logo
Masuhr, J., Klompmaker, F., Reimann, C., & Nebe, K
(2008) Designing context-aware in-car information systems. In Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services (Mobiquitous ‘08) , 1–8. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering). DOI logo
Miluk-Kolasa, B., Matejek, M., & Stupnicki, R
(1996) The effects of music listening on changes in selected physiological parameters in adult pre-surgical patients. Journal of Music Therapy, 33(8), 208–218. DOI logoGoogle Scholar
Mokbel, M., & Levandoski, J
(2009) Toward context and preference-aware location-based services. In Eighth ACM International Workshop on Data Engineering for Wireless and Mobile Access , 25–32. ACM. DOI logo
Rauterberg, G
(2006) Hci as an engineering discipline: To be or not to be!? African Journal of Information and Communication Technology, 2(4), 163–184. DOI logoGoogle Scholar
Rentfrow, P., & Gosling, S
(2003) The do re mi’s of everyday life: The structure and personality correlates of music preferences. Journal of Personality and Social Psychology, 84(6), 1236–1256. DOI logoGoogle Scholar
Rubens, N., Kaplan, D., & Sugiyama, M
(2011) Active learning in recommender systems. In Recommender Systems Handbook, 735–767. Springer. DOI logoGoogle Scholar
Sarwar, B., Karypis, G., Konstan, J., & Reidl, J
(2001) Item-based collaborative filtering recommendation algorithms. In 10th International Conference on World Wide Web (WWW ‘01) , 285–295, New York. ACM. DOI logo
Siddiqi, R
(2011) The world of 21st century in-flight entertainment. Aviation & Tourism (FRIDAY, 19 AUGUST 2011) in The Independent.Google Scholar
Steelman, V
(1991) Relaxing to the beat: Music therapy in perioperative nursing. Today’s OR Nurse, 13(7), 18.Google Scholar
Stratton, V., & Zalanowski, A
(1984) The relationship between music, degree of liking, and self-reported relaxation. Journal of Music Therapy, 21(4), 184–192. DOI logoGoogle Scholar
Su, J., Yeh, H., Yu, P., & Tseng, V (2010) Music recommendation using content and context information mining. Intelligent Systems, IEEE, 25(1), 16–26. DOI logoGoogle Scholar
Su, X., & Khoshgoftaar, T
(2009) A survey of collaborative filtering techniques. Advances in Artificial Intelligence, 2009, 1–19 (Article ID 421425). DOI logoGoogle Scholar
Suh, Y., Park, Y., Yoon, H., Chang, Y., & Woo, W
(2007) Context-aware mobile ar system for personalization, selective sharing, and interaction of contents in ubiquitous computing environments. In J. Jacko (ed.), Human-Computer Interaction. Interaction Platforms And Techniques, Lecture Notes in Computer Science, 966–974. Springer Berlin/Heidelberg. DOI logoGoogle Scholar
Taelman, J., Vandeput, S., Spaepen, A., & Huffel, S
(2009) Influence of mental stress on heart rate and heart rate variability. In J. Sloten, P. Verdonck, M. Nyssen, & J. Haueisen (eds.), 4th European Conference of the International Federation for Medical and Biological Engineering, volume 22 of IFMBE Proceedings , 1366–1369. Springer Berlin Heidelberg. DOI logoGoogle Scholar
White, J., & Shaw, C
(1991) Music therapy: A means of reducing anxiety in the myocardial infarction patient. Wisconsin Medical Journal, 90(7), 434–437.Google Scholar
Witmer, B., & Singer, M
(1998) Measuring presence in virtual environments: A presence questionnaire. Presence, 7(3), 225–240. DOI logoGoogle Scholar
Woerndl, W., Schueller, C., & Wojtech, R
(2007) A hybrid recommender system for context-aware recommendations of mobile applications. In 2007 IEEE 23rd International Conference on Data Engineering Workshop , 871–878. Istanbul. DOI logo
World Health Organization
(2005) Travel by air: Health considerations, in International travel and health: Situation as on 1 January 2005. World Health Organization. DOI logoGoogle Scholar
Yoshii, K., Goto, M., Komatani, K., Ogata, T., & Okuno, H
(2006) Hybrid collaborative and content-based music recommendation using probabilistic model with latent user preferences. In 7th International Conference on Music Information Retrieval (ISMIR) , 296–301.
Cited by

Cited by 5 other publications

Chaudhari, Kinjal & Ankit Thakkar
2020. A Comprehensive Survey on Travel Recommender Systems. Archives of Computational Methods in Engineering 27:5  pp. 1545 ff. DOI logo
Feng, Yuan, Ruud van Reijmersdal, Suihuai Yu, Matthias Rauterberg, Jun Hu & Emilia Barakova
2018. Dynamorph: Montessori Inspired Design for Seniors with Dementia Living in Long-Term Care Facilities. In Intelligent Technologies for Interactive Entertainment [Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 215],  pp. 49 ff. DOI logo
Lee, Wei-Po, Chun-Ting Chen, Jhih-Yuan Huang & Jhen-Yi Liang
2017. A smartphone-based activity-aware system for music streaming recommendation. Knowledge-Based Systems 131  pp. 70 ff. DOI logo
Motamedi, Elham
2021. Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization,  pp. 304 ff. DOI logo
Motamedi, Elham & Marko Tkalčič
2023. User-centric item characteristics for personalized multimedia systems: A systematic review. Intelligenza Artificiale 17:2  pp. 207 ff. DOI logo

This list is based on CrossRef data as of 1 may 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.