Browse > Article
http://dx.doi.org/10.17661/jkiiect.2021.14.3.215

A Study on Intelligent Emotional Recommendation System Using Biological Information  

Kim, Tae-Yeun (National Program of Excellence in Software center, Chosun University)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.14, no.3, 2021 , pp. 215-222 More about this Journal
Abstract
As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.
Keywords
Biological information; Emotion; Recommendation system; Ontology; Zigbee;
Citations & Related Records
연도 인용수 순위
  • Reference
1 C. K. Kim, J. H. Son, S. G. Lee, J. H. Cha and S. H. Kim, "A Study on Emotional Vocabulary for Interactive Visual Media Viewing Behavior Models Construction", Journal of Korea Design Forum, vol. 54, no. 54. pp. 27-38, Jan, 2017.
2 T. Y. Kim, H. Ko, S. H. Kim and H. D. Kim, "Modeling of Recommendation System Based on Emotional Information and Collaborative Filtering", Sensors, vol. 21, no. 6, 1997, March, 2021.
3 W. Su, O. B. Akan and E. Cayirci, "Communication Protocol for Sensor Networks, Wireless Sensor Network", Kluwer Academic Publisher, pp. 21-50, 2004.
4 D. W. Seo, B. H. Song, H, Seo and S. H. Bae, "Design and Implementation of Bio Emotion Recognition LED Control System by Stress Index using Neural Network", Journal of Advanced Information Technology and Convergence, vol. 8, no. 12, pp. 221-229, Nov, 2010.
5 J. S. An, K. N. Kang, S. H. Kim and K. I. Song, "Analysis for Applicability of Differential Evolution Algorithm to Geotechnical Engineering Field", Journal of the Korean Geotechnical Society, vol. 35, no. 4, pp. 27-35, April, 2019.   DOI
6 D. Amer, B. Samira and B. Imene, "A sinusoidal differential evolution algorithm for numerical optimisation", Applied Soft Computing, vol. 27, pp. 98-126, Feb, 2015.
7 L. Tang, Y. Zhao and J. Liu, "An Improved Differential Evolution Algorithm for Practical Dynamic Scheduling in Steelmaking-Continuous Casting Production", IEEE Transactions on Evolutionary Computation, vol. 18, no. 2, pp. 209-225, April, 2014.   DOI
8 W. J. Seo and K. T. Rhyu, "Design and Implementation of Information Retrieval System Based on Ontology Using Semantic Web", Journal of Digital Convergence, vol. 17, no. 1, pp. 209-217. Jan, 2019.   DOI
9 D. J. Choi, H. B. Lee, K. S. Bok and J. S. Yoo, "Design and implementation of an academic expert system through big data analysis", The Journal of Supercomputing, pp. 1-25, Jan, 2021.
10 T. Y. Kim, B. H. Song and S. H. Bae, "A Design and Implementation of Music & Image Retrieval Recommendation System based on Emotion", Journal of the Institute of Electronics Engineers of Korea, vol. 47, no. 1, Jan, 2010.
11 E. H. Kim and Y. H. Suh, "A Situation Information Model based on Ontology in IoT Environment". Journal of Korea institute of information, electronics, and communication technology, vol. 10, no. 5, pp. 380-388, Oct, 2017.   DOI
12 R. W. Picard, "Affective computing: challenges", International Journal of Human-Computer studies, vol. 59, no. 1, pp. 55-64, July, 2003.   DOI
13 M S. Kim and Y. C. Cho, "GSR, HRV and EEG ANalysis of Stress Caused by Horror Image and Noise Stimulation", Journal of IKEEE, vol. 21, no. 4, pp. 4381-4387, Dec, 2017.
14 J. Y. Chung and M. J. Kim, "A Study on Personalized Music Recommendation Model through Analysis on Users' Music Preference Factors", Journal of Digital Contents Society, vol. 19, no, 11, pp. 2041-2047, Nov, 2018.   DOI
15 A. Y. Kim, E. H. Jang and J. H. Sohn, "Classification of Negative Emotions based on Arousal Score and Physiological Signals using Neural Network", Korean Society for Emotion and Sensibility, vol. 21, no. 1, pp. 177-186, March, 2018.   DOI
16 Y. S. Lee, "Study on ERP Detection Algorithm Using SVM with wavelet feature vector", The Journal of Korea Institute of Information, Electronics, and Communication Technology, vol. 10, no. 1, pp. 9-15, Jan, 2017.   DOI
17 H. Wang, T. Vincent and C. Tang, "Change propagation analysis for system modeling using Semantic Web technology", Advanced Engineering Informatics, vol. 35, pp. 17-29, Jan, 2018.   DOI