박사

사용자 성향과 상품 신뢰도를 고려한 뷰티 빅데이터 기반의 개인화 추천 및 검색 시스템 = Personalized Recommendation and Search System Based on Beauty Big Data Considering User Preferences and Item Reliability

송재오 2019년
논문상세정보
' 사용자 성향과 상품 신뢰도를 고려한 뷰티 빅데이터 기반의 개인화 추천 및 검색 시스템 = Personalized Recommendation and Search System Based on Beauty Big Data Considering User Preferences and Item Reliability' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • 검색
  • 뷰티
  • 빅데이터
  • 사용자성향
  • 상품신뢰도
  • 추천
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
2,816 0

0.0%

' 사용자 성향과 상품 신뢰도를 고려한 뷰티 빅데이터 기반의 개인화 추천 및 검색 시스템 = Personalized Recommendation and Search System Based on Beauty Big Data Considering User Preferences and Item Reliability' 의 참고문헌

  • “The beauty of big data: the L’Or al and IBM story”, latest version at http://www.ibmbigdatahub.com/blog/, last accessed 06 May 2018.
  • “Marketing Revolution, Social Influencer Marketing”, Oversea Market News of KOTRA, 2017.
  • “L'Or al selects Siemens' PLM software to improve product and process innovation”, latest version at https://www.siemens.com/press/, last accessed 06 May 2018.
  • “4th Industrial Revolution, Manufacturing Innovation and Smart Factory, Oversea Market News of KOTRA, 2017.
  • https://www.amazon.com, 2018.
  • https://play.google.com/store/apps/details?id=com.k_ict.KosBig
  • https://ko.wikipedia.org/wiki/TF-IDF
  • https://dev.twitter.com/streaming/overview
  • http://ekbia.or.kr, 2013.
  • http://display.cjmall.com, 2018.
  • Yeonwoo Noh, Jomgtae Lim, Kyoungsoo Bok, Jaesoo Yoo, “Hot Topic Prediction Scheme Using Modified TF-IDF in Social Network Environments”, Journal of KIISE Transactions on Computing Practices, Vol.23, No.4, pp,217-225, 2017.
  • Y. Wang, J. Zhou and H. Tan, "CC-PSM: A Preference-Aware Selection Model for Cloud Service Based on Consumer Community", Mathematical Problems in Engineering, 2015.
  • Y. Jiang, J. Liu, M. Tang, and X. Liu, "An effective web service recommendation method based on personalized collaborative filtering," Proceedings of International Conference on In Web Services, pp.211-218, 2011.
  • Y. A. Kim and G. W. Park, “Topic-Driven SocialRank: Personalized search result ranking by identifying similar, credible users in a social network," International Journal of Knowledge-Based Systems, Vol.54, pp.230-242, 2013.
  • Xuehua Shen, Bin Tan, ChengXiang Zhai, “Implicit user modeling for personalized search”. Proceedings of International Conference on Information and Knowledge Management, pp.824-831, 2005.
  • T. Ha and S. Lee, "Item network based collaborative filtering: A personalized recommendation method based on a user's item network," Information Processing and Management, Vol.53, No.5, pp.1171-1184, 2017.
  • T. Ebesu and Y. Fang, "Neural Semantic Personalized Ranking for item cold start recommendation," Information Retrieval Journal, Vol.20, No.2, pp.109-131, 2017.
  • Susan Gauch, Jason Chaffee, Alexander Pretschner, “Ontology-based personalized search and browsing”, Web Intelligence and Agent Systems, Vol.1, No. 3-4, pp.219-234, 2003.
  • So-Young Yun, Sung-Dae Youn, “Recommendation System Using Big Data Processing Technique”, Journal of the Korea Institute of Information and Communication Engineering, Vol.21, No.6, pp.1183-1190, 2017.
  • Shengliang Xu, Shenghua Bao, Ben Fei, Zhong Su, Yong Yu, “Exploring folksonomy for personalized search”, Proceedings of Annual ACM Conference on Research and Development in Information Retrieval, pp.155-162. 2008.
  • S. Xu, S. Bao, B. Fei, Z. Su, and Y. Yu, “Exploring folksonomy for personalized search,” Proceedings of ACM SIGIR International Conference on Research and Development in Information Retrieval, pp.155-162, 2008.
  • S. Huang, Y. Chen, H. Chen, L. Chen, and Y. Fan, "Personalized item of interest recommendation on storage constrained smartphone based on word embedding quantization," Proceedings of Pacific Asia Conference on Knowledge Discovery and Data Mining, pp.610-621, 2018.
  • S. Bao, G. Xue, X. Wu, Y.Yu, B. Fei and Z.Su, “Optimizing Web Search Using Social Annotations," Proceedings of International Conference on World Wide Web, pp.501-510, 2007.
  • RuiGuo Yu, ManKun Zhao, Peng Chang, and MuWen He, “Online hot topic detection from web news archive in short terms”, Proceedings of International Conference on Fuzzy Systems and Knowledge Discovery, pp.919-923, 2014.
  • R. Baeza Yates and B. Ribeiro Neto, Modern information retrieval, ACM press, 1999.
  • R. Abdelkhalek, I. Boukhris, and Z. Elouedi, "Assessing items reliability for collaborative filtering within the belief function framework," Proc. International Conference on Digital Economy, pp.208-217, 2017.
  • Paolo Ferragina, Antonio Gulli, “A Personalized Search Engine Based on Web-Snippet Hierarchical Clustering”, Proceedings of International World Wide Web Conference, pp.801-810, 2005.
  • P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, “Grouplens: an open architecture for collaborative filtering of Netnews,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, New York, pp.175-186, 1994.
  • O. Shafiq, R. Alhajj and John G. Rokne, “On personalizing Web search using social network analysis,” International Journal of Information Sciences, Vol.314, pp.55-76, 2015.
  • M. Claypool, P. Le, M. Waseda, and D. Brown, “Implicit interest indicators,” Proceedings of International Conference on Intelligent User Interfaces, pp.33-40, 2001.
  • Kyung-Joong Kim, Sung-Bae Cho, “Development of a Personalized Link-based Search Engine using Fuzzy Concept Network”, Journal of Journal of the Korea Institute of Information Scientists and Engineers, Vol.7, No.3, pp.211-219, 2001.
  • Kyoung Soo Bok, Min Je Ahn, Jong Tae Lim, Jae Soo Yoo, “Efficient Location Based Social Search Considering Time Property in Mobile Environments”, Journal of the Korea Institute of Information Scientists and Engineers, Vol.20, No.4, pp.243-247, 2014.
  • Kim Jae-Kyeong, Ahn Do-Hyun, Cho Yoon-Ho, ”Development of a Personalized Recommendation Procedure Based on Data Mining Techniques for Internet Shopping Malls“, Journal of Korea Intelligent Information Systems Society, Vol.9, No.3, pp.177-191, 2003.
  • JinWoo Song, Hyeonwook Jeon, Minsoo Kim, Gihoon Kim, Yeonwoo Noh, Jongtae Lim, Kyoungsoo Bok, Jaesoo Yoo, “Social Search Scheme Considering Recent Preferences of Social Media Users”, International Journal of Contents, Vol.17, No.2, pp.113-124, 2017.
  • Jaehak Jung, “Key to the era of the 4th Industrial Revolution, Software Quality”, Issue Report of NIPA, No.7, 2017.
  • J. Markus, H. Rainer, and D. Andreas, “On the Evaluation of Document Analysis Components by Recall, Precision, and Accuracy,” Proceedings of International Conference on Document Analysis and Recognition, pp.713-716, 1999.
  • J. Beel, M. Genzmehr, S. Langer, A. Nurnberger, and B. Gipp, "A comparative analysis of offline and online evaluations and discussion of research paper recommender system evaluation," Proceedings of International workshop on reproducibility and replication in recommender systems evaluation, pp.7-14, 2013.
  • Hwi-Gang Kim, Seongjoo Lee, and Sunghyon Kyeong, “Discovering Hot Topics using Twitter Streaming Data”, Proceedings of International Conference on Advances in Social Networks Analysis and Mining, pp.1215-1220, 2013.
  • Haziq Jeelani and Khushal Singh, “‘Good’ versus ‘Bad’ Opinion on Micro Blogging Networks: Polarity Classification of Twitter”, International Journal of Computer Science and Mobile Computing, Vol.3, No.8, pp.49-56, 2014.
  • Geonsik Ko, Byounghoon Kim, Daeyun Kim, Minwoong Choi, Jongtae Lim, Kyoungsoo Bok, Jaesoo Yoo, “Contents Recommendation Scheme Considering User Activity in Social Network Environments”, International Journal of Contents, Vol.17, No.2, pp.404-414, 2017.
  • Feng Qiu, Junghoo Cho, “Automatic identification of user interest for personalized search”, Proceedings of International World Wide Web Conference, pp.727-736, 2006.
  • Dong-Kyun Lee, Joon Hee Kwon, “Social Search Algorithm considering Recent Interests of User”, Journal of Advanced Information Technology and Convergence, Vol.9, No.4, pp.187-194, 2011.
  • Dojin Choi, Minsoo Kim, Daeyun Kim, Seohee Lee, Jinsu Han, Indeok Seo, Jongtae Lim, Kyoungsoo Bok, Jaesoo Yoo, “Design and Implementation of an Expert Search System Using Academic Data in Big Data Processing Platforms”, International Journal of Contents, Vol.17, No3, pp.100-114, 2017.
  • D. Horowitz and D.Kamvar, “The Anatomy of a LargeScale Social Search Engine," Proceedings of International Conference on World Wide Web, pp.431-440, 2010.
  • Chang-Woo Song, Jong-Hun Kim, Kyung-Yong Chung, Joong-Kyung Ryu, Jung-Hyun Lee, “Contents Recommendation Search System using Personalized Profile on Semantic Web”, International Journal of Contents, Vol.8, No1, pp.318-327, 2008.
  • Byeong Man Kim, Qing Li, Si-Gwan Kim, En Ki Lim, Ju-Yeon Kim, “A New Approach Combining Content-based Filtering and Collaborative Filtering for Recommender Systems”, Journal of KIISE, Vol.31, No.3, pp.332-341, 2004.
  • B. Palese and A. Usai, "The relative importance of service quality dimensions in e commerce experiences," International Journal of Information Management, Vol.40, pp.132-140, 2018.
  • B. J. Corbitt, T. Thanasankit, and H. Yi, "Trust and e commerce: a study of consumer perceptions," Electronic commerce research and applications, Vol.2, No.3, pp.203-215, 2003.
  • B. Carterette and R. Jones, “Evaluating Web Search Engines Using Clickthrough Data," Proceedings of ACM SIGIR International Conference, 2007.
  • Alessandro Micarelli, Fabio Gasparetti, Filippo Sciarrone, Susan Gauch, "Personalized Search on the World Wide Web", Lecture Notes in Computer Science. Vol.4321, pp.195-230. 2007.
  • A. Parasuraman, V. A. Zeithaml, and L. L. Berry, "Servqual: A multiple item scale for measuring consumer perc," Journal of retailing, Vol.64, No.1, pp.12-31, 1988.
  • A. Kashyap, R. Amini and V. Hristidis, “SonetRank: Leveraging Social Networks to Personalize Search,” Proceedings of ACM International Conference on Information and knowledge management, pp.2045-2049, 2012.