Journal of the Korea Society of Computer and Information最新文献_第5页

Deterministic Parallelism for Symbolic Execution Programs based on a Name-Freshness Monad Library 基于名称更新Monad库的符号执行程序的确定性并行性

Journal of the Korea Society of Computer and Information Pub Date : 2021-02-01 DOI: 10.9708/JKSCI.2021.26.02.001

Ki Yung Ahn

引用次数: 0

Improvement of Processing Speed for UAV Attitude Information Estimation Using ROI and Parallel Processing 利用ROI和并行处理提高无人机姿态信息估计处理速度

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.155

Ha Seok Wun, Park Myeong Chul

引用次数: 0

A Research on Paramedic Student Type of Perception for 119 Rescue Workers 急救学生对119救援人员感知类型的研究

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.08.127

Jae-min Lee

引用次数: 0

Development and application of Scenario-based Admission Management VR contents for nursing students 面向护生的场景化招生管理VR内容开发与应用

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.209

Kim Yu Jeong

引用次数: 8

A Study on GAN Algorithm for Restoration of Cultural Property (pagoda) 文物(宝塔)修复的GAN算法研究

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.077

Jin-Hyun Yoon, Byong-Kwon Lee, Byung-Wan Kim

引用次数: 1

A research on the possibility of restoring cultural assets of artificial intelligence through the application of artificial neural networks to roof tile(Wadang) 人工神经网络应用于瓦片修复人工智能文化资产的可能性研究(瓦当)

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.019

JunOh Kim, Lee Byong Kwon

引用次数: 1

The Effects of Digital Consumption Trust and Corporate Trust on IT Device and Service Satisfaction 数字消费信任和企业信任对IT设备和服务满意度的影响

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.217

Park Seung Bae, Hong Jaewon

引用次数: 0

Improvement of a Product Recommendation Model using Customers' Search Patterns and Product Details 基于顾客搜索模式和产品详细信息的产品推荐模型改进

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.265

Lee Yunju, Lee, Jaejun, Ahn, Hyunchul

{"title":"Improvement of a Product Recommendation Model using Customers' Search Patterns and Product Details","authors":"Lee Yunju, Lee, Jaejun, Ahn, Hyunchul","doi":"10.9708/JKSCI.2021.26.01.265","DOIUrl":"https://doi.org/10.9708/JKSCI.2021.26.01.265","url":null,"abstract":"[Abstract] In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers’ purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.","PeriodicalId":17254,"journal":{"name":"Journal of the Korea Society of Computer and Information","volume":"9 1","pages":"265-274"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87727638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Secure Training Support Vector Machine with Partial Sensitive Part 部分敏感部件的安全训练支持向量机

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.04.001

Saerom Park

{"title":"Secure Training Support Vector Machine with Partial Sensitive Part","authors":"Saerom Park","doi":"10.9708/JKSCI.2021.26.04.001","DOIUrl":"https://doi.org/10.9708/JKSCI.2021.26.04.001","url":null,"abstract":"In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.","PeriodicalId":17254,"journal":{"name":"Journal of the Korea Society of Computer and Information","volume":"21 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81836419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Possibility of Neural Network Approach to Solve Singular Perturbed Problems 神经网络方法求解奇异摄动问题的可能性

Journal of the Korea Society of Computer and Information Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.069

Jee-Hyun Kim, Young-Im Cho

引用次数: 0