김재경 교수

For one company to have a competitive advantage and sustainability over others, its human resource management is of the utmost importance to secure competent employees. As job satisfaction plays a critical role in securing excellent manpower and enhancing corporate performance, it is essential to identify factors that would affect employees’ job satisfaction. Recently, writing reviews with integrity on job portal sites by former and current employees has become prevalent as such websites have gu

Numerous reviews are posted every day on travel information sharing platforms and sites. Hotels want to develop a customer recommender system to quickly and effectively identify potential target customers. TripAdvisor, the travel website that provided the data used in this study, allows customers to rate the hotel based on six criteria: Value, Service, Location, Room, Cleanliness, and Sleep Quality. Existing studies classify reviews into positive, negative, and neutral by extracting sentiment te

The advertising market’s use of smartphones and kiosks for non-face-to-face ordering is growing. An advertising video recommender system is needed that continuously shows advertising videos that match a user’s taste and displays other advertising videos quickly for unwanted advertisements. However, it is difficult to make a recommender system to identify users’ dynamic preferences in real time. In this study, we propose an advertising video recommendation procedure based on computer vision and d

Online reviews that consist of texts and images are an essential source of information for alleviating data sparsity in recommender system studies. Although texts and images provide different types of information, they can provide complementary or substitutive advantages. However, most studies are limited in introducing the complementary effect between texts and images in the recommender systems. Specifically, they have overlooked the informational value of images and proposed recommender system

Review helpfulness prediction aims to provide helpful reviews for customers to make purchase decisions. Although many studies have proposed prediction mechanisms, few have introduced consistency between the review text and star rating information in the review helpfulness prediction task. Moreover, previous studies that have reflected such a consistency still have limitations, including the star rating facing information loss, and the interaction between review text and star rating not extracted

In this study, socioeconomic, medical treatment, and health check-up data from 2010 to 2017 of the National Health Insurance Service (NHIS) of Korea were analyzed. This year's socioeconomic, treatment, and health check-up data are used to develop a predictive model for high medical expenses in the next year. The characteristic of this study is to derive important variables related to the high cost of domestic medical expenses users by using data on health check-up items conducted by the country.

Abstract With the rapid growth of the e‐commerce market facilitated, users are often overwhelmed by the excessive online information, making item selection challenging. While recommendation services have significantly enhanced user experience and sales, these traditional models often overlook the complexity of user‐item interactions and user preferences based on various item aspects. The proposed AXCF framework innovatively combines graph‐based collaborative filtering (CF), which captures high‐o

Purpose Because the food service industry is more dependent on customer contact and human resources than other industries, it is crucial to understand the factors influencing employee job satisfaction to ensure that employees provide satisfactory service to customers. However, few studies have incorporated employee reviews of job portals into their research. Many job seekers tend to trust company reviews posted by employees on job portals based on the information provided by the company itself.

This study explores the determinants of job satisfaction among IT industry employees in the U.S. and South Korea, focusing on how cultural and socio-economic contexts influence employee well-being and organizational sustainability. Given the high turnover rates in the IT industry, understanding the key factors affecting job satisfaction and dissatisfaction is critical for promoting sustainable organizational practices. By comparing reviews from Glassdoor and Jobplanet, this study uncovers cultur

ABSTRACT Collaborative filtering is a widely used method in recommender systems research. However, contrary to the assumption that it relies solely on rating data, many contemporary models incorporate review information to address issues such as data sparsity. Although previous recommender systems utilised review texts to capture user preferences and item features, they often rely on a single‐embedding model to represent these features, which may limit the richness of the extracted information.

With the increase in insured patients and an aging population, managing the length of stay (LOS) for inpatients has become crucial for controlling medical costs. Analyzing the factors influencing LOS is necessary for effective management. Previous studies often used multiple or logistic regression analyses, which have limitations such as unmet assumptions and the inability to handle time-dependent variables. To address these issues, this study applied survival analysis to examine the factors aff

The rapid growth of e-commerce has made both companies and customers face a new situation. Whereas companies have become to be harder to survive due to more and more competitions, the opportunity for customers to choose among more and more products has increased. So, the recommender systems that recommend suitable products to the customer have an important position in E-commerce. This research introduces collaborative filtering based recommender system which helps customers find the products the

Intelligent Decision System support the decision analysis process in the managerial problems with decision analytic knowledge as well as domain specific knowledge. Influence Diagram has been one of the major knowledge representation in the intelligent decision system. In the development of intelligent decision system, knowledge acquisition is also known to be difficult. This paper suggests a developing tool using an influence diagram and Verbal Protocol Analysis which facilitates knowledge acqui

One of the most difficult and time-consuming stages in the development of the knowledge-based system is a knowledge acquisition. A splitting algorithm is developed to infer a rule-tree which can be converted to a rule-typed knowledge. A market segmentation may be performed in order to establish market strategy suitable to each market segment. As the sales data of a product market is probabilistic and noisy, it becomes necessary to prune the rule-tree-at an acceptable level while generating a rul