• The Journal of the Korea Contents Association
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• v.14 no.7
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• pp.29-44
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• 2014

To provide context aware service, certain phenomena and situation information of the user should be detecting and monitoring using sensors. But, the sensor data has heterogeneity about system, syntax, structure, and semantics. So, it is difficult to apply to various services. To solve this issue, we should remove these heterogeneities and convert to context information that is easy to provide context aware services. Also, the existing context aware service mash-up environment require relevant sensor type, criteria of context, programing ability to define the service situation. So, it is difficult to create service for a non-technical user. Therefore, we propose ontology based user-centric service environment to provide context aware IoT services. It provide context awareness and user-desired services using data that acquired via IoT paradigm. The proposed environment consist of the ontology based semantic sensor data processing and the user-centric service environment. It provide convert the object data to the context information and service mash-up process to create user service in easy way.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.143-150
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• 2021

There is a need for an artificial intelligent technology that can reduce various types of safety accidents by analyzing the risk factors that cause safety accidents in industrial site. In this paper, user safety profiling methods are proposed that can prevent safety accidents in advance by specifying and modeling user information data related to safety accidents. User information data is classified into normal and abnormal conditions through deep learning based artificial intelligence analysis. As a result of verifying user safety profiling technology using more than 10 types of industrial field data, 93.6% of user safety profiling accuracy was obtained.

• Journal of Fashion Business
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• v.26 no.1
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• pp.1-15
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• 2022

Digital transformation has induced changes in human life patterns; consumption patterns are also changing to digitalization. Entering the era of industry 4.0 with the 4th industrial revolution, it is important to pay attention to a new paradigm in the fashion industry, the shift from developer-centered to user-centered in the era of the 3rd industrial revolution. The meaning of storing users' changing life and consumption patterns and analyzing stored big data are linked to consumer sentiment. It is more valuable to read emotions, then develop and distribute products based on them, rather than developer-centered processes that previously started in the fashion market. An AI(Artificial Intelligence) deep learning algorithm that analyzes user emotion big data from user experience(UX) to emotion and uses the analyzed data as a source has become possible. By combining AI technology, the fashion industry can develop various new products and technologies that meet the functional and emotional aspects required by consumers and expect a sustainable user experience structure. This study analyzes clear and useful user experience in the fashion industry to derive the characteristics of AI algorithms that combine emotions and technologies reflecting users' needs and proposes methods that can be used in the fashion industry. The purpose of the study is to utilize information analysis using big data and AI algorithms so that structures that can interact with users and developers can lead to a sustainable ecosystem. Ultimately, it is meaningful to identify the direction of the optimized fashion industry through user experienced emotional fashion technology algorithms.

• Journal of Information Technology Services
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• v.21 no.3
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• pp.1-25
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• 2022

The financial MyData service has implemented in January 2022 and launched 45 services by banks, securities, credit cards and fintech companies. This study applied the Q methodology, to identify the user types of MyData services and compared the perceptions of employees of financial institutions who plan and develop the MyData services. There are three types of MyData service users: active users, limited users who focus on consumption and asset status inquiry, and sensitive users for personal information. There were two types of recognition of financial company employees. One is the active user support other is the sensitive user for personal information support. The analysis of subjective perceptions can be used as a reference for establishing a company's MyData service marketing strategy and establishing related policies to improve the MyData ecosystem.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.58.2-58
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• 2001

• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.71-84
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• 2007

The architecture for RFID-based home network and an intelligent agent for efficiently managing home network are proposed in this paper. The agent consists of six modules-Agent Manager, Data Collector, Execution Controller, Data Storage, Data Queue and User Interface. Agent Manager manages the tasks of modules, and Data Collector collects the data from home appliances through the RFID readersm Execution Controller determines the operations home appliances according to the conditions of the home environment and transfers the operations to the appliances through the RFID readers. Moreover, Data Storage keeps the data which is necessary for the operations of the agent, and Data Queue temporarily stores the data which is collected from home appliances. Lastly, User Interface provides the graphical user interface in which an individual can directly control and monitor the home network. The proposed intelligent agent autonomously learns the circumstances of a home network by analyzing the data about the state of home appliances, and controls home appliances according to the preference of the user. Therefore, the user can live in the best-suited home environment without direct appliance control if he/she performs home networking through the agent.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.249-252
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• 2009

Recently, it is possible for users to acquire necessary data easily as the various schemes of the searching information are developed. Since these data rise continuously like stream data, it is required to extract the appropriate data for the user's needs from the mass data on the internet. In the traditional scheme, they are acquired by processing the user queries after the occurred data are stored at a database. However, it is inefficient to process the user queries over the large volume of continuous data by using the traditional scheme. In this paper, we propose the query processing scheme to extract the data efficiently for the user requirements from the large volume of continuous data. On the proposed scheme, we present the Event-Profile Model to define the data occurrence on the internet as the events and the user's requirements as the profiles. We also show the filtering scheme to process the events and the profiles efficiently.

• Archives of design research
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• v.20 no.2 s.70
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• pp.5-16
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• 2007

The main objective of our research is analyzing user's emotional changes while using a product, to reveal the influence of usability on human emotions. In this study we have extracted some emotional words that can come up during user interaction with a product and reveal emotional changes through three methods. Finally, we extracted 88 emotional words for measuring user's emotions expressed while using products. And we categorized the 88 words to form 6 groups by using factor analysis. The 6 categories that were extracted as a result of this study were found to be user's representative emotions expressed while using products. It is expected that emotional words and user's representative emotions extracted in this study will be used as subjective evaluation data that is required to measure user's emotional changes while using a product. Also, we proposed the effective methods for measuring user's emotion expressed while using a product in the environment which is natural and accessible for the field of design, by using the emotion mouse and the Eyegaze. An examinee performs several tasks with the emotion mouse through the mobile phone simulator on the computer monitor connected to the Eyegaze. While testing, the emotion mouse senses user's EDA and PPG and transmits the data to the computer. In addition, the Eyegaze can observe the change of pupil size. And a video camera records user's facial expression while testing. After each testing, a subjective evaluation on the emotional changes expressed by the user is performed by the user him/herself using the emotional words extracted from the above study. We aim to evaluate the satisfaction level of usability of the product and compare it with the actual experiment results. Through continuous studies based on these researches, we hope to supply a basic framework for the development of interface with consideration to the user's emotions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.154-163
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• 2017

Collaborative filtering, one of the most widely used techniques to build recommender systems, is based on the idea that users with similar preferences can help one another find useful items. Credit card user behavior analytics show that most customers hold three or less credit cards without duplicates. This behavior is one of the most influential factors to data sparsity. The 'cold-start' problem caused by data sparsity prevents recommender system from providing recommendation properly in the personalized credit card recommendation scenario. We propose a personalized credit card recommender system to address the cold-start problem, using multiple user profiles. The proposed system consists of a training process and an application process using five user profiles. In the training process, the five user profiles are transformed to five user networks based on the cosine similarity, and an integrated user network is derived by weighted sum of each user network. The application process selects k-nearest neighbors (users) from the integrated user network derived in the training process, and recommends three of the most frequently used credit card by the k-nearest neighbors. In order to demonstrate the performance of the proposed system, we conducted experiments with real credit card user data and calculated the F1 Values. The F1 value of the proposed system was compared with that of the existing recommendation techniques. The results show that the proposed system provides better recommendation than the existing techniques. This paper not only contributes to solving the cold start problem that may occur in the personalized credit card recommendation scenario, but also is expected for financial companies to improve customer satisfactions and increase corporate profits by providing recommendation properly.

• Journal of the Korean Institute of Educational Facilities
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• v.24 no.6
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• pp.37-44
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• 2017

This study is about user satisfaction of the Junior College Library based on its characteristics of space composition. For this, we studied characteristics of space composition targeting the libraries in colleges in Seoul and Gyeonggi-do. First, in case of study of characteristics of space composition for books and library data, student satisfaction for traditional and normal library areas was high. It means that the service based on library areas should start from normal library areas as well as there is a change about space as the type of data in libraries change to electric data and multimedia. Second, If we look at the space for a reader and a user, satisfaction for a normal reading room was high. we can also see that satisfaction for a computer room and a multimedia reading room was not higher but still high. Also, the reason why satisfaction for a multimedia reading room that provides various activities was high was that the complex of a library space is needed to provide users with various activities. Third, in case of space for programme function and meeting, satisfaction for the room of video information and the group study room was high. we can see that user satisfaction for the space got high basically when a user is satisfied with the proper information technology based on interaction Fourth, as a result of variance analysis of 3 spaces of Junior College Library and the services, the size of the space of service does not influence user satisfaction directly. Even the space is small, if it decorates variously like with a lighting for a user, a window seat to meet the nature of users and has specific factors such as space reservation using internet, user satisfaction is high. If we summarise the result of this study, to make user satisfaction for speace in a Junior College Library higher, not just we need to try to make it extend as a educational, a cultural place but we also need to accept the student's requirement that the space also needs to be extend as a complex cultural space.