• Knowledge Management Research
• /
• v.22 no.4
• /
• pp.27-40
• /
• 2021

Click-Through Rate (CTR) prediction is a key function that determines the ranking of candidate items in the recommendation system and recommends high-ranking items to reduce customer information overload and achieve profit maximization through sales promotion. The fields of natural language processing and image classification are achieving remarkable growth through the use of deep neural networks. Recently, a transformer model based on an attention mechanism, differentiated from the mainstream models in the fields of natural language processing and image classification, has been proposed to achieve state-of-the-art in this field. In this study, we present a method for improving the performance of a transformer model for CTR prediction. In order to analyze the effect of discrete and categorical CTR data characteristics different from natural language and image data on performance, experiments on embedding regularization and transformer normalization are performed. According to the experimental results, it was confirmed that the prediction performance of the transformer was significantly improved when the L2 generalization was applied in the embedding process for CTR data input processing and when batch normalization was applied instead of layer normalization, which is the default regularization method, to the transformer model.

• Knowledge Management Research
• /
• v.24 no.1
• /
• pp.73-97
• /
• 2023

Recently, the MyData market has been growing as the importance of data and issues related to personal information protection have drawn much attention together. MyData refers to the concept of guaranteeing an individual's right to personal information and providing and utilizing one's data according to individual consent. MyData service providers can combine and analyze customer information to provide personalized services. In the early days, the MyData business was activated mainly by private companies and the financial industry, but recently, public institutions are also actively taking advantage of MyData. Meanwhile, the importance of an individual's intention to provide MyData for the success of MyData businesses continues to increase, but research related to this is lacking. Moreover, existing studies have been mainly conducted on individual benefits of MyData; there are not enough studies in which both public benefit and perceived risk factors are considered at the same time. In this regard, this study intends to derive factors affecting the intention to provide MyData based on the privacy calculus model, examine their influencing mechanism, and further verify the moderating effects of individual capabilities and institutional type. This study can find academic significance in that it expanded and demonstrated the privacy calculus model in the context of MyData providing intention. In addition, the results of this study are expected to offer practical guidelines for developing and managing new services in MyData businesses.

• Journal of Digital Convergence
• /
• v.12 no.4
• /
• pp.319-326
• /
• 2014

According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

• Culinary science and hospitality research
• /
• v.20 no.2
• /
• pp.120-135
• /
• 2014

This research aimed to investigate the effect of business management of Korean restaurants on business performance and to propose an alternative. For this investigation, a survey was carried out targeting Korean restaurant managers in the capital area, and with 360 copies as sample, factor analysis, difference test, and multiple regression analysis were conducted. As a result of analysis, among the factors of business management of Korean restaurants, only information management and fund management appeared to have effects on both financial performance and nonfinancial performance. This means, in case of Korean restaurants, business performance can be improved by understanding every environment about food service management and customer demands, by investing fund in the right place, and by managing inefficient expenses. Therefore, it is most important for a Korean restaurant manager to cultivate knowledge in management and to put effort into cost-reduction of all employees.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.4
• /
• pp.1923-1931
• /
• 2014

A value creation is understood as important business strategy these days in both academics and industry. But this phenomenon is not fully understood based on systematized framework. In this paper, we summarized value research trend based on exploratory research and inductive reasoning by exploring both international and domestic journals. And we built a research framework that can analyze value creation between supplier and customer. Value research prior to 2004 is primarily divided into values of goods or services and relationship values. After 2004, service-dominant (SD) logic has been outlined. There are other research trends to see the relationship value in terms of relationship benefits and relationship in the network or supply chain. 4 critical resource types (financial resource, knowledge resource, efficiency resource, and intellectual resource) and 5 competence types (relational capability, collaboration capability, innovation capability, managing capability) are constructed as principal factors for value creation from inductive reasoning based upon a resource-based view (RBV) and a competence-based view (CBV). The research framework was built based on 4 resources and 4 competences.

• Fashion & Textile Research Journal
• /
• v.14 no.5
• /
• pp.791-802
• /
• 2012

This study promotes education, purchase, and advertisement activities related to eco-friendly apparel products. The study examined college students and their demographic characteristics, their recognition of and interest in, knowledge, purchase, and attitude towards advertisements related to eco-friendly apparel products. In this study, 337 students from various universities in Daejeon participated in a questionnaire survey from March 7 to March 25, 2011. The collected materials were analyzed by frequency analysis, factor analysis, cluster analysis, cross tabulations analysis, and t-test using SPSS 18.0 software. The results of these tests revealed that more students from the upper grades belonged to the Environmentally Friendly Group compared to those in the Non-environmentally Friendly Group. It was also found that students in the Environmentally Friendly Group had a higher level of consciousness and expressed a greater interest in eco-friendly apparel products as well as towards the launch of educational programs. Additionally, this group was more supportive of the need for new courses and had a higher likelihood to enroll in these courses. The research results revealed that (compared to the Non-environmentally Friendly Group) the Environmentally Friendly Group exhibited a greater satisfaction with the designs of eco-friendly apparel products and had more experience to examine advertisements about eco-friendly apparel products; in addition, they expressed a higher likability and reliability to these advertisements. The results also showed that the Environmentally Friendly Group believed that advertisements had persuasive power and were quite impressive in recalling the advertisements.

• Spatial Information Research
• /
• v.13 no.3 s.34
• /
• pp.239-252
• /
• 2005

The major reason that spatial data warehousing has attracted a great deal of attention in business GIS in recent years is due to the wide availability of huge amount of spatial data and the imminent need for fuming such data into useful geographic information. Therefore, this research has been focused on designing and implementing the pilot tested system for spatial decision making. The purpose of the system is to predict targeted marketing area by discriminating the customers by using both transaction quantity and the number of customer using credit card in department store. Moreover, the pilot tested system of this research provides OLAP tools for interactive analysis of multidimensional data of geographically various granularities, which facilitate effective spatial data mining. focused on the analysis methodology, the case study is aiming to use GIS and clustering for knowledge discovery. Especially, the importance of this study is in the use of snowflake schema model capabilities for GIS framework.

• Journal of Information Technology Services
• /
• v.19 no.4
• /
• pp.31-47
• /
• 2020

Recently, as the COVID-19 has spread and prolonged worldwide, the 'Untact' society is becoming routinized, and various smart technologies are leading to the spread of the 'Ontact' culture. This is because the desire of consumers to purchase a product and use the service has increased while minimizing the direct contact. In order to quickly respond to this circumstance, the percentage of the companies which are adopting Chatbot in various fields such as orders, delivery, and inquiries is increasing and they are getting a positive result. However as the demand for building Chatbot increases dramatically, there are many confusions among the companies which want to introduce Chatbot to their system, due to the lack of professional technicians and difficulties in understanding AI technologies and how to build them effectively. I believe that in the post COVID-19 era, much more companies will adopt Chatbot, and this will intensify the problem. The purpose of this study was to derive the needs for a guide on the method of buiilding a Chatbot through considering the prior research on Chatbot and analysis of the recent surge in the use of Chatbot services related to COVID-19. There are implications to presenting 5 phases of universal Chatbot implementation methodology using the platform to the stakeholders who want to introduce Chatbot to their customer so that they can understand and build Chatbot more easily and use AI Chatbot actively in response to the POST COVID-19 era.

• Journal of Distribution Science
• /
• v.14 no.11
• /
• pp.129-138
• /
• 2016

Purpose - The ICT(information and communications technologies) development is affecting consumer behaviors on selecting channel or distribution system. This study aims to advance our knowledge about the factors influencing omni-channel behaviors. This study considers the positive brand experience as the moderating variable into the relationship between omini-channel use intention and consumer brand relation. Also, the effect of positive brand experience on consumer-brand relation is researched. Research design, data, and methodology - This study conducted an empirical test with the subject as customers who purchase goods or service through on-off cross channel simultaneously. The research model is developed from prior literatures about influencing variables on channel selection. The structure of this study is designed to identify causal relationships between the variables. 268 survey data from the questionnaire survey which is conducted to target customers who use online and offline channels, is used for empirical analysis. This study validates generality with descriptive statistics and data reliability with Cronbach's alpha value. The exploratory factor analysis is used for value purification. Then, the confirmatory factor analysis is conducted for structural equation modeling. Finally, the execute structural equation modeling is analyzed to confirm the hypotheses Results - First, the two causal influences between perceived performance risk and the propensity of omni-channel and between price consciousness and the propensity of omni-channel are verified through the empirical test. Second, the result identifies that the propensity of omni-channel is influenced on consumer-brand relationship. Third, the AMOS analysis proves that the moderating variable, positive brand experience, has significant positive impact on consumer-brand relationship. This significant relationship is highly supported by the regression analysis between brand experience and propensity of omni-channel because it results that positive brand experience has positive impact on the propensity of omni-channel. All hypotheses are verified to be true. Conclusions - Based on the empirical result, this study confirms that perceived performance risk and price consciousness are the important factors influencing propensity of omni-channel. According to the additional analysis, the moderating variable and positive brand experience plays important role between the propensity of omni-channel and consumer-brand relationship. Furthermore, positive brand experience influences more on consumer-brand relationship than non-positive brand experience.

• Journal of Internet Computing and Services
• /
• v.13 no.1
• /
• pp.65-74
• /
• 2012

Cloud services are used for improving business. Moreover, customer relationship management(CRM) approaches use social networking as tools to enhance services to customers. However, most cloud systems do not support the semantic structures, and because of this, vital information from social network sites is still hard to process and use for business strategy. This paper proposes a collaboration framework based on social semantic web for cloud system. The proposed framework consists of components to support social semantic web to provide an efficient collaboration system for cloud consumers and service providers. The knowledge acquisition module extracts rules from data gathered by social agents and these rules are used for collaboration and business strategy. This paper showed the implementations of processing of social network site data in the proposed semantic model and pattern extraction which was used for the virtual grouping of cloud service providers for efficient collaboration.