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http://dx.doi.org/10.3745/KTSDE.2022.11.11.447

Personalized Clothing and Food Recommendation System Based on Emotions and Weather  

Ugli, Sadriddinov Ilkhomjon Rovshan (순천향대학교 컴퓨터소프트웨어공학과)
Park, Doo-Soon (순천향대학교 컴퓨터소프트웨어공학과)
Publication Information
KIPS Transactions on Software and Data Engineering / v.11, no.11, 2022 , pp. 447-454 More about this Journal
Abstract
In the era of the 4th industrial revolution, we are living in a flood of information. It is very difficult and complicated to find the information people need in such an environment. Therefore, in the flood of information, a recommendation system is essential. Among these recommendation systems, many studies have been conducted on each recommendation system for movies, music, food, and clothes. To date, most personalized recommendation systems have recommended clothes, books, or movies by checking individual tendencies such as age, genre, region, and gender. Future generations will want to be recommended clothes, books, and movies at once by checking age, genre, region, and gender. In this paper, we propose a recommendation system that recommends personalized clothes and food at once according to the user's emotions and weather. We obtained user data from Twitter of social media and analyzed this data as user's basic emotion according to Paul Eckman's theory. The basic emotions obtained in this way were converted into colors by applying Hayashi's Quantification Method III, and these colors were expressed as recommended clothes colors. Also, the type of clothing is recommended using the weather information of the visualcrossing.com API. In addition, various foods are recommended according to the contents of comfort food according to emotions.
Keywords
Recommendation System; Emotion; Clothing; Food; Weather; SNS;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 P. Vilakone, K. Xinchang, and D. S. Park, "Movie recommendation system based on users' personal information and movies rated using the method of k-clique and normalized discounted cumulative gain," Journal of Information Processing Systems, Vol.16, No.2, pp.494-507, 2020.   DOI
2 S. Park, B. Bae, and Y. Cheong, "Emotion recognition from text stories using an emotion embedding model," IEEE International Conference on Big Data and Smart Computing (BigComp), pp.579-583, 2020.
3 P. Ekman, "An argument for basic emotions," Cognition And Emotion, Vol.6, pp.169-200, 1992.   DOI
4 표정을 보면 감정을 읽을 수 있을까 [Internet], https://www.dong ascience.com/news.php?idx=35206
5 J. R. L. Bernard, "The Macquarie Thesaurus," Australia, Macquarie Library Pty Ltd, 2007.
6 Twitter [Internet], http://twitter.com.
7 DataReportal, "Digital 2021 global digital overview," 2021.
8 A. Felfernig, V. M. Le, A. Popescu, M. Uta, T. N. T. Tran, and M. Atas, "An overview of recommender systems and machine learning in feature modeling and configuration," In 15th International Working Conference on Variability Modelling of Software-Intensive Systems(VaMoS'21), Association for Computing Machinery, New York, NY, USA, Article 16, pp.1-8.
9 J. K. Tarus, Z. Niu, and D. Kalui, "A hybrid recommendation system for e-learning based on context awareness and sequential pattern mining," Soft Computing, Vol.22, No.8, pp.2449-2461, 2018.   DOI
10 K. Haruna et al., "Context-aware recommender system: A review of recent developmental process and future research direction," Applied Sciences, Vol.7, No.12, pp.1211, 2017.   DOI
11 M. J. Kim, D. S. Park, M. Hong, and H. M. Lee, "Personalized movie recommendation system using context-aware collaborative filtering technique," KIPS Transactions on Computer and Communication Systems, Vol.4, No.9, pp.289-296, 2015.   DOI
12 Facebook [Internet], http://facebook.com.
13 Instagram [Internet], https://www.instagram.com.
14 K. Sailunaz and R. Alhajj, "Emotion and sentiment analysis from Twitter text," Journal of Computational Science, Vol. 36, pp.1-18, 2019.
15 R. Majid and H. A. Santoso, "Conversations sentiment and intent categorization using context RNN for emotion recognition," 7th International Conference on Advanced Computing and Communication Systems (ICACCS), pp.46-50, 2021.
16 K. Jia and Z. Li, "Chinese micro-blog sentiment classification based on emotion dictionary and semantic rules," International Conference on Computer Information and Big Data Applications (CIBDA), pp.309-312, 2020.
17 H. Kwak, C. Lee, H. Park, and S. Moon, "What is twitter, a social network or a news media?," Proceedings of the 19th International Conference on World Wide Web, ACM, April, pp.591-600, 2010.
18 T. M. Kim, "A research on the color application method in the product design through the quantification theory of type III to interpret sensibility information," Master's thesis, The University of Seoul, 2009.
19 먹으면 우울한 식품 vs 기분좋은 식품 [Internet], http://www.mindgil.com/news/articleView.html?idxno=68844
20 S. Mohammad and P. Turney, "Emotions evoked by common words and phrases: Using mechanical turk to create an emotion lexicon," Proceedings of the NAACL-HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, LA, California, 2010.
21 위로를 먹는다, '컴포트 푸드' [Internet], https://www.foodnews.news/news/article.html?no=216465
22 S. Joshi and D. Deshpande, "Twitter sentiment analysis system," International Journal of Computer Applications, Vol.180, No.47, pp.35-39, 2018.
23 F. Long, "Improved personalized recommendation algorithm based on context-aware in mobile computing environment," Wireless Communication and Mobile Computing, Hindawi, pp.1-10, 2020.
24 기온별 옷차림, 4도~28도까지 기온 및 계절별 옷차림 정보는?... 오늘(10일) 자켓.야상 필수! [Internet], http://www.kyeongin.com/main/ view.php?key=20181010000733388
25 슬플 때.화날 때.우울할 때 먹는 음식? 감정별 상황별 효과 있는 '컴포트 푸드' [Internet], https://m.blog.naver.com/PostView.naver?isHttpsRedirect=true&blogId=kfcc_no1& logNo=221079601681
26 Y. Wang, "Emotions extracted from text vs. true emotions-an empirical evaluation in SE context," 34th IEEE/ACM International Conference on Automated Software Engineering (ASE), pp.230-242, 2019.
27 G. S. Park, "Movie recommendation system using SNS data and collaborative filtering algorithm," Chonnam National University Master's thesis, 2017.