• Journal of the Korean Home Economics Association
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• v.41 no.9
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• pp.69-83
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• 2003

Today, because of the consumers who should constantly decide which to buy in a flood of information can't search for complete information by the limited time and the lack of the ability in evaluating the goods, the price being important as the information clue in consumers' goods or dependence on the price will be gradually increasing. The purpose of this study is to know how much price sensitivity recognized by consumers will have and effect on buying feeling of satisfaction in internet shopping mall. The result of this study is that the consumers' target-oriented behavior searching appropriate price for buying goods in internet shopping mall substantially elevates the price sensitivity and shapes the positive attitude toward the feeling of satisfaction. It is meaningful in that it has provided the base for studying the price sensitivity centering around some limited factors through actual proof of how the consumers respond to the price at this point of activating online transactions.

• The Journal of Information Systems
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• v.26 no.4
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• pp.285-301
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• 2017

Purpose In this paper we verified the reliabilities of healthcare-related information provided by various users on the site of Naver Jisikin, a Korean typical search platform. Based on Q&A contents we validated answers' reliabilities to the asked questions about a lung cancer with the help of professors at a medical school. Design/methodology/approach The content analysis includes that the types of questions are classified into symptom/diagnosis, therapy, prognosis, after-management and so on. The answers contains advice, advertisement, oriental medicine, and religion as well as the above 5 question categories. The validation results of medical evidence about each answer show that only 49% among all answers have medical grounds. Findings We classified the medical grounded answers into three levels; high, medium and low. Among all answers we need to find out the answers including advertisement because the answers can be harmful to patients. We found the method to select the answers containing advertisement contents with the help of text mining research. The selection model presents high performance as 84% classification accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.602-604
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• 2011

Due to wide usage of smartphones and mobile internet, mobile devices are used in various fields such as sending SMS, participating SNS, retrieving information and the number of users taking advantage of them are growing. The keypads of a mobile device are relatively smaller than those of desktop computers. Thus, the user has a difficulty in input sentences quickly and correctly. In this study, we introduce some string recommendation and modification techniques which can be used for helping a user input in mobile devices quickly and correctly. We describe a TRIE dictionary and n-gram language model which are the main technologies of the keyword recommendation applied to the online search engines.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3258-3275
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• 2015

The rise in recent technology has changed the ways, in which people communicate with one another. Social networking services (SNSs) have become one of the most representative means. General SNSs allow users to create their own unique profiles, search for fellow members, share information, etc., while other SNSs have functions that cater to different needs of users. As a result, users of SNSs have begun to pick and choose different SNSs and concurrently use multiple SNSs in order to fulfill all their needs. This exploratory study examined which SNSs are used together and the characteristics that predict the use of multiple SNSs. In addition, it observed the differences between consumers' usage of multiple SNSs in different cultures. An online survey was administered to SNS users in the United States and Korea. The results of the study showed that the use of multiple SNSs is not yet prevalent in Korea, the country that represented a collectivistic culture. In addition, in the U.S., the highest number of users reported that they were active on at least three SNSs.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.245-257
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• 2022

In the Internet of Things (IoT) era, the types of devices used by one user are becoming more diverse and the number of devices is also increasing. However, a forensic investigator is restricted to exploit or collect all the user's devices; there are legal issues (e.g., privacy, jurisdiction) and technical issues (e.g., computing resources, the increase in storage capacity). Therefore, in the digital forensics field, it has been a challenge to acquire information that remains on the devices that could not be collected, by analyzing the seized devices. In this study, we focus on the fact that multiple devices share data through account synchronization of the online platform. We propose a novel way of identifying the user's interest through analyzing the remnants of targeted advertising which is provided based on the visited websites or search terms of logged-in users. We introduce a detailed methodology to pick out the targeted advertising from cache data and infer the user's interest using deep learning. In this process, an improved learning model considering the unique characteristics of advertisement is implemented. The experimental result demonstrates that the proposed method can effectively identify the user interest even though only one device is examined.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.730-744
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• 2023

The topic of this paper is the recognition of human activities using egocentric vision, particularly captured by body-worn cameras, which could be helpful for video surveillance, automatic search and video indexing. This being the case, it could also be helpful in assistance to elderly and frail persons for revolutionizing and improving their lives. The process throws up the task of human activities recognition remaining problematic, because of the important variations, where it is realized through the use of an external device, similar to a robot, as a personal assistant. The inferred information is used both online to assist the person, and offline to support the personal assistant. With our proposed method being robust against the various factors of variability problem in action executions, the major purpose of this paper is to perform an efficient and simple recognition method from egocentric camera data only using convolutional neural network and deep learning. In terms of accuracy improvement, simulation results outperform the current state of the art by a significant margin of 61% when using egocentric camera data only, more than 44% when using egocentric camera and several stationary cameras data and more than 12% when using both inertial measurement unit (IMU) and egocentric camera data.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.147-163
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• 2004

For the purchase of a cheaper product on the Internet, many customers have been trying to search online shopping mall sites and visit comparison-pricing shops that compare prices and other criteria of the product. Others have been participating into online auction markets or group-buying markets. However, a lot of online shopping malls, auction markets, and group-buying markets provide the same product with different prices. Since these marketplaces have different price settlement mechanism, it is very difficult for the customers to determine marketplace to purchase, considering different kinds of marketplaces at the same time. To overcome such limitations, decision rules and solution procedures for purchase decision making are necessary, which can cover multiple marketplaces simultaneously. For this purpose, purchase decision making in each market must be conducted to maximize customer's utility, and conflicts with other marketplaces must be resolved. Therefore, we have developed the rules and methods that can negotiate cooperatively the purchase decision making in several marketplaces, and designed an architecture of Intelligent Buyer Agent and a message structure to support the idea.

• Information Systems Review
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• v.7 no.1
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• pp.97-113
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• 2005

This paper designed and implemented(programmed) a comparative shopping agent that helps consumers to shop at on-line shopping malls over Internet. At offline stores, as consumers usually tell a sales clerk about a manufacturer, functions and price range of an item they want to purchase, the sales clerk will show the products or relevant catalogues. Then the consumer will compare functions, design and prices of the product and buy it with the lowest price. PriceMeter, a comparative shopping agent, introduced in this paper, is designed best geared to this consumers' buying behavior. Basically, as consumers enter a manufacturer's name, price, features and etc. at a search window, PriceMeter will search the web and provide a list of product informations such as features and prices that meet the search conditions. Consumers can see the information in either a form of catalogue or a printing format. As consumers click specific items to examine closely, it will show prices and information about shopping malls that sell the requested items. Clicking a 'Buy' icon, the consumers will be transferred to the right web page at the linked shopping mall. The emergence of the comparative shopping agent will expedite a consumer-centered retailing economy in the age of e-commerce. As consumers are provided with a better set of product and shopping mall information, they can make better purchasing decisions and gain more bargaining power shifted from manufacturers(sellers). The presentation of this comparative shopping agent is intended to promote the consumer-centered B2C e-commerce.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.777-787
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• 2020

With the development of the Internet and the spread of mobile devices, the online market is growing rapidly. As the number of customers using online shopping malls explodes, research is being conducted on the analysis of usage behavior from customer data, personalized product recommendations, and service development. Thus, this paper seeks to analyze the overall process of online shopping malls through process mining, and to identify the factors that influence users' purchases. The data used are from a large online shopping mall, and R was the analysis tool. The results show that customer activity was most prominent in categories with event elements, such as unconventional discounts and monthly giveaway events. On the other hand, searches, logins, and campaign activity were found to be less relevant than their importance. Those are very important, because they can provide clues to a customer's information and needs. Therefore, it is necessary to refine the recommendations from related search words, and to manage activity, such as coupons provided when customers log in. In addition to the previous discussion, this paper proposes various business strategies to enhance the competitiveness of online shopping malls and to increase profits.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.388-397
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• 2012

Recently, one of the received attraction fields in web based service is 'Human Relationship Service' that is called SNS. This relationship map service is able to deliver information to user more easily and visually because it is intuitive data that is linked with offline real world. While past map service put physical real information in the map, present map service is evolving into new communicative platform that expresses social relationship beyond simple search platform that shows real world. In this paper, we propose smart social grid system using sketch map that is based on online map service structure. This system has features such as standardized interface provision for various SNS, use to governance hub tool in case of establishing a personal network through expanded social grid, a role of bridge to mashup software linked with other SNS, user environment construction that reproduces social grid data, and the faster service setup by improved search technology.