• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.1-24
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• 2010

Most of enterprises depend on a data modeler during developing their management information systems. In formulating business requirements for information systems, they widely and naturally use the interview method between a data modeler and a field worker. But, the discrepancy between both parties would certainly cause information loss and distortion that lead to let the systems not faithful to real business works. To improve or avoid modeler-dependant data modeling process, many automated data design CASE tools have been introduced. However, since most of traditional CASE tools just support drawing works for conceptual data design, a data modeler could not generate an ERD faithful to real business works and a user could not use them without any knowledge on database. Although some CASE tools supported conceptual data design, they still required too much preliminary database knowledge for a user. Against these traditional CASE tools, we proposed a Requirement-Oriented Entity Relationship Model for automated data design tool, called ROERM. Based on Non-Stop Methodology, ROERM adopts inner systematic modules for complete and sound ERD that is faithful to real field works, where modules are composed of interaction modules with a user, rules of schema operations and sentence translations. In addition to structure design of ROERM, we also devise detailed algorithms and perform an experiment for a case study.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.25-40
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• 2022

This study is about how the quality of M2M big data that provides real-time information affects users. Recently, there are many difficulties in acquiring and managing data because data types such as variety, data volume, and data velocity are changing rapidly and diversified. This not only leads to a decrease in data quality but also it can give a negative impact when making decisions using data. Generally, the quality of data is defined as 'suitability for use', which means that data quality must meet the expectations of user needs. Therefore, data providers need activities to improve data quality for this purpose, and the key is to identify data quality dimensions in each field where data is used and provide data suitable for the level of user needs. In this study, the relationship between the quality area of real-time M2M data used in the traffic information system and user satisfaction was analyzed. Research models and hypotheses were established to analyze the effects between variables related to M2M big data. In order to test the hypothesis, a causal relationship between the major factors was identified by conducting a survey and analyzing the data users.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.493-498
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• 2024

With the rapid advancement of generative artificial intelligence technology, there is growing interest in how to utilize it in practical applications. Additionally, the importance of prompt engineering to generate results that meet user demands is being newly highlighted. Exploring the new possibilities of generative AI can hold significant value. This study aims to utilize ChatGPT 4.0, a leading generative AI, to propose an effective method for evaluating user experience through the analysis of online customer review data. The user experience evaluation method was based on the six-layer elements of user experience: 'functionality', 'reliability', 'usability', 'convenience', 'emotion', and 'significance'. For this study, a literature review was conducted to enhance the understanding of prompt engineering and to grasp the clear concept of the user experience hierarchy. Based on this, prompts were crafted, and experiments for the user experience evaluation method were carried out using the analysis of collected online customer review data. In this study, we reveal that when provided with accurate definitions and descriptions of the classification processes for user experience factors, ChatGPT demonstrated excellent performance in evaluating user experience. However, it was also found that due to time constraints, there were limitations in analyzing large volumes of data. By introducing and proposing a method to utilize ChatGPT 4.0 for user experience evaluation, we expect to contribute to the advancement of the UX field.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.843-849
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• 2003

Web usage mining is the technique of data mining that analyzes web users' usage patterns by large web log. To use the web usage mining technique, we have to classify correctly users and users session in preprocessing, but can't classify them completely by only log files with standard web log format. To classify users and user session there are many problems like local cache, firewall, ISP, user privacy, cookey etc., but there isn't any definite method to solve the problems now. Especially local cache problem is the most difficult problem to classify user session which is used as input in web mining systems. In this paper we propose a heuristic method which solves local cache problem by using only click stream data of server side like referrer log, agent log and access log, classifies user sessions and completes session.

• The Journal of the Korea Contents Association
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• v.7 no.8
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• pp.94-101
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• 2007

In this paper, we propose a surveillance system using multi-person tracking in a WIPI based mobile system, which is the standard wireless internet platform. The proposed system consists of two subsystems: the person tracking system and the mobile information transmission system. The person tracking system tracks persons who invade security and the mobile information transmission system sends the tracking results from the person tracking system to the user's mobile phone. In this paper, the person tracking system tracks persons who appear on many cameras with non-overlapping views in order to achieve a wider view. The mobile information transmission system saves automatically tracked data to the owner's web server and transmits the saved data to the user's WIPI mobile phone. Therefore, whenever the user wishes to view tracked data later, the mobile system can provide the user with the tracking results by either the user selecting particular cameras or the time on the owner's mobile phone. The proposed system is a new surveillance system that transfers tracked data among cameras to the user's mobile phone in order to overcome space limitations in tracking areas and monitoring areas and spatial limitations in monitoring hours.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.857-866
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• 2003

For detecting an intrusion based on the anomaly of a user's activities, previous works are concentrated on statistical techniques in order to analyze an audit data set. However. since they mainly analyze the average behavior of a user's activities, some anomalies can be detected inaccurately. In this paper, a new clustering algorithm for modeling the normal pattern of a user's activities is proposed. Since clustering can identify an arbitrary number of dense ranges in an analysis domain, it can eliminate the inaccuracy caused by statistical analysis. Also, clustering can be used to model common knowledge occurring frequently in a set of transactions. Consequently, the common activities of a user can be found more accurately. The common knowledge is represented by the occurrence frequency of similar data objects by the unit of a transaction as veil as the common repetitive ratio of similar data objects in each transaction. Furthermore, the proposed method also addresses how to maintain identified common knowledge as a concise profile. As a result, the profile can be used to detect any anomalous behavior In an online transaction.

• The Journal of Information Systems
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• v.29 no.2
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• pp.95-110
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• 2020

Purpose This paper attempts to explain the recent expanding trend in Mobile Grocery Shopping(MGS). More specifically, the authors have applied the Post Acceptance Model(PAM) in order to examine the conceptual structure among the four constructs of 'Expectation Confirmation', 'Perceived Usefulness', 'User Satisfaction', and 'Continuance Intention to Use' in Mobile Grocery Shopping. Design/methodology/approach Through a survey agency, data were collected from a sample of 312 consumers who had the previous experience in Mobile Grocery Shopping. The Structural Equation Modeling(SEM) analysis was conducted with the survey data using AMOS 22.0. Subsequently, 8,200 real customer data from an open market site were collected in order to find out their revisit and repurchase behavior. Findings This study supported the causal relationships of Expectation Confirmation → Perceived Usefulness, Expectation Confirmation → User Satisfaction, Perceived Usefulness → User Satisfaction, and User Satisfaction → Continuance Intention to Use, but did not support the direct effect of Perceived Usefulness on the Continuance Intention to Use Mobile Grocery Shopping. This implies that consumers with any experience in Mobile Grocery Shopping would not consider repurchase, unless they are satisfied with the experience even though they perceive its usefulness. Also, Expectation Confirmation has much larger effect on User Satisfaction than Perceived Usefulness. In addition, the real customer data showed that the revisit and the repurchase rate of mobile grocery shoppers were higher than those of online grocery shoppers, although the rates of adding to shopping carts, coupon downloads, and adding to favorites are similar.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.82-86
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• 2012

In For the past few years, query log data has been collected to find user's behavior in using the site. Many researches have studied on the usage of query logs to extract user's preference, recommend personalization, improve caching and pre-fetching of Web objects, build better adaptive user interfaces, and also to improve Web search for a search engine application. A query log contain data such as the client's IP address, time and date of request, the resources or page requested, status of request HTTP method used and the type of browser and operating system. A query log can offer valuable insight into web site usage. A proper compilation and interpretation of query log can provide a baseline of statistics that indicate the usage levels of website and can be used as tool to assist decision making in management activities. In this paper we want to discuss on the tasks performed of query logs in pre-processing of web usage mining. We will use query logs from an online newspaper company. The query logs will undergo pre-processing stage, in which the clickstream data is cleaned and partitioned into a set of user interactions which will represent the activities of each user during their visits to the site. The query logs will undergo essential task in pre-processing which are data cleaning and user identification.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.372-377
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• 2006

In this paper, we propose sensibility recognition model that recognize user's sensibility using brain waves. Method to acquire quantitative data of brain waves including priority living body data or sensitivity data to recognize user's sensitivity need and pattern recognition techniques to examine closely present user's sensitivity state through next acquired brain waves becomes problem that is important. In this paper, we used pattern recognition techniques to use Multi Layer Perceptron (MLP) that is pattern recognition techniques that recognize user's sensibility state through brain waves. We measures several subject's emotion brain waves in specification space for an experiment of sensibility recognition model's which propose in this paper and we made a emotion DB by the meaning data that made of concentration or stability by the brain waves measured. The model recognizes new user's sensibility by the user's brain waves after study by sensibility recognition model which propose in this paper to emotion DB. Finally, we estimates the performance of sensibility recognition model which used brain waves as that measure the change of recognition rate by the number of subjects and a number of hidden nodes.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.629-637
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• 2022

This study is an experiment on the use of RDW(Redirected Walking) technology, which helps users to hardly feel the difference of user movement in the limited physical space and the extended virtual space when the user moves while wearing the HMD in the real world. The RDW function installed in 3D space realization software such as Unity3D is used to induce the user's redirection by slightly distorting the virtual space according to the user's point of view. However, if the RDW distortion rate is used excessively, dissonance is highly likely to occur. In particular, it is easy to make errors that cause cybersickness of users. It is important to obtain the RDW data value in the virtual environment so that the user does not feel fatigue and cybersickness even after wearing the HMD for a long time. In this experiment, it was tested whether the user's RDW was safely implemented, and item and obstacle arrangement data were obtained through this experiment. The RDW data obtained as a result of the experiment were used for item placement and obstacle placement in the virtual space.