• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.257-266
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• 2014

In this paper, we propose the development of an eBook Service System based on VOD Broadcasting Contents(eBSS-VOD) which protects the illegal copy through the effective DRM strategy. Here, eBSS-VOD is composed of three sub-systems - eBook server management system, ePub Builder, and eBook App - according to the functional points of view. The eBook server management system operates to manage the eBooks, the encription keys, the VOD contents, the membership and the history of users' viewing log. The ePub Builder assists to produce eBooks by DRM strategy. The eBook App provides users with the utility services of VOD viewing and eBook purchase processing. The proposed eBSS-VOD, differently from the current eBook systems, helps to increase the users' interests in reading books and to motivate the users' purchasing needs and it also makes new distribution channel for eBooks based on VOD broadcasting contents through smart applications. We provides the differentiated eBook builder which are based on ePub3.0 and DRM strategy. Through empirical survey results on users' interests and purchase intention for eBooks, we show that the proposed eBSS-VOD has the comparative effects compared to the current systems.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.163-172
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• 2012

Collaborative filtering which is used explicit method in a existing recommedation system, can not only reflect exact attributes of item but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. This paper proposes the personalized recommendation system using RFM method and k-means clustering in u-commerce which is required by real time accessablity and agility. In this paper, using a implicit method which is is not used complicated query processing of the request and the response for rating, it is necessary for us to keep the analysis of RFM method and k-means clustering to be able to reflect attributes of the item in order to find the items with high purchasablity. The proposed makes the task of clustering to apply the variable of featured vector for the customer's information and calculating of the preference by each item category based on purchase history data, is able to recommend the items with efficiency. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.12
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• pp.1667-1673
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• 2008

This study was conducted to investigate the purchase behavior of environment-friendly agricultural products (EFATs) and to provide necessary information for planning and executing effective marketing strategies for producers and distributors. The subjects of this study were 306 housewives in the Seoul area over the age of 20. The result of this study showed that once a month topped with 38.9% in the frequency of purchase, vegetables were the highest with 83.3% in the percentage of purchase and the place of purchase most frequented by consumers discount stores (45.8%), but purchases from farmers were the lowest with 3.6%. TV/radio topped the list of information resource with 3.42, followed by family/relatives/friends (3.33) and newspaper/ magazine (3.31). Those surveyed listed sanitary condition/freshness (4.43), safety (4.20), nutrition (4.05), and taste (3.99) as major evaluative criteria for choosing organic food, in order of importance. Finally, consumers seem to be satisfied with the nutrition (3.75), safety (3.71), and freshness (3.70) of the products and they were dissatisfied with the price of the products.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.159-171
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• 2018

The imported foods, which are imported and sold domestically, are on the rise every year, and the scale is expected to be larger, including processing the imported raw materials. However, the origin of raw materials is indicated when declaring cargo for finished products of agricultural products, but the standardization of inspection information management system for raw materials is insufficient. In addition, there is a growing concern about the presence of residual pesticides or radioactivity in raw materials or products, and customer want to know production history information when purchasing agrifoods. It manages the hazard analysis of imported agricultural products, but most of them are global issues such as microorganisms, residual pesticides, food additives, and allergy components, etc. Therefore, it is necessary to share among the logistics entities in the entire transportation process the related data. Additionally, to do this, it needs to design an architecture and standardize business model. In this paper, it defines the architecture and the work-flow that occurs between the business process for collecting, processing, and processing information for tracking the status of imported agricultural products by steps, and develops XML message with UBL and the extracted conceptual information model. It will be easy to exchange and share information among the logistics entities through the defined standard model and it will be possible to establish visibility, reliability, safety, and freshness system for transportation of agricultural products requiring real-time management.

• Information Systems Review
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• v.14 no.1
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• pp.37-65
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• 2012

This research aims to design and analyze a ubiquitous customer relationship management system based on near field communication which can be applied to stores in off-line environment. The existing customer relationship management system has been used mainly for stores in off-line environment to issue a royalty card, to stamp a seal on the purchase goods, and to manage the history of customers' visits and purchases. But, the existing system has two weaknesses; it makes difficult for a store manger not only to acquire a wealth of customer data but also to systematically manage the acquired data. In particular, the effectiveness and efficiency of the royalty card are questioned when a customer makes purchases in the store in that the customer frequently does not carry it or loses it. So, this research suggests a ubiquitous customer relationship management system where a tag for near field communications is attached to a store in off-line environment; a store manager can collect and manage easily customer's dada and customers can seamlessly acquire store's information. To do this, this research conducts the followings. First, we review the previous researches of customer relationship management to examine the concept of ubiquitous customer relationship management. Second, from the examination, we draw the factors to be considered in ubiquitous customer relationship management system based on near field communication. Third, we propose a scenario where the suggested system is used. Fourth, we analyze the participants' values and the process that will be used for the suggested system. Finally, we discuss the possibility of the application of this system to real business environment from various viewpoints.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.265-274
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• 2021

In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.96-104
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• 2020

As consumers' consumption activities become more active due to the activation of online shopping malls, companies are conducting item trend analyses to boost sales. The existing item trend analysis methods are analyzed by considering only the activities of users in online shopping mall services, making it difficult to identify trends for new items without purchasing history. In this paper, we propose a trend analysis method that combines data in online shopping mall services and social network data to analyze item trends in users and potential customers in shopping malls. The proposed method uses the user's activity logs for in-service data and utilizes hot topics through word set extraction from social network data set to reflect potential users' interests. Finally, the item trend change is detected over time by utilizing the item index and the number of mentions in the social network. We show the superiority of the proposed method through performance evaluations using social network data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1139-1145
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• 2018

According to the prosecutors' office's statistics for 2014, 53% of a bicycle users have experienced theft. The reason for the high rate of bicycle stolen in Korea is that there is no bicycle management system. This is because they do not use bicycle numbers to manage bikes like cars do. Most people do not know if they have a VIN(Vehicle Identification Number) on their bike. If the buyer registers the bicycle in the bicycle management blockchain system, anyone can view the information registered in the chain, so that if the bicycle number is filled in, the bicycle can be identified. In addition, when an accident occurs, blockchain will record what kind of equipment it is replacing, like an automobile, to manage all the information about the bicycle. In this way, consumers can inquire whether they have a history of accident when they make a second-hand transaction. In this paper, we propose a method to construct bicycle management system using bicycle VIN.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.301-314
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• 2001

Data mining refers to a set of techniques for discovering implicit and useful knowledge from large database. Many studies on data mining have been pursued and some of them have involved issues of temporal data mining for discovering knowledge from temporal database, such as sequential pattern, similar time sequence, cyclic and temporal association rules, etc. However, all of the works treat problems for discovering temporal pattern from data which are stamped with time points and do not consider problems for discovering knowledge from temporal interval data. For example, there are many examples of temporal interval data that it can discover useful knowledge from. These include patient histories, purchaser histories, web log, and so on. Allen introduces relationships between intervals and operators for reasoning about relations between intervals. We present a new data mining technique that can discover temporal relation rules in temporal interval data by using the Allen's theory. In this paper, we present two new algorithms for discovering algorithm for generating temporal relation rules, discovers rules from temporal interval data. This technique can discover more useful knowledge in compared with conventional data mining techniques.

• Korean Public Health Research
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• v.44 no.4
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• pp.15-24
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• 2018

Objective : This study explores whether and how the amount of smoking differs by economic status and perception among the men in working age. Methods : The study utilized the 4th wave of KoWEPS containing the items on perception of economic conditions. Analysis was conducted on ever-married men aged 30-54, who have capacity to work. It used 2 stage regression model methods to examine the mediation effect of perception on economic status. Results : The results shows that the negative perception on economic status has a positive effect on smoking. Disposable income affects smoking only through the perception of economic status. Employment status exerts both direct and indirect effect on smoking. Conclusions : These findings imply that less privileged economic status is related to smoking through anxiety or stress for the negative perception on it.