• Journal of Information Technology Applications and Management
• /
• v.23 no.4
• /
• pp.55-70
• /
• 2016

Recently, development of indoor positioning system and IoT such as beacon makes it possible to collect and analyze each customer's shopping behavior in off-line shopping malls. In this study, we propose a realtime brand recommendation scheme based on each customer's brand visiting history for off-line shopping mall with indoor positioning system. The proposed scheme, which apply collaborative filtering to off-line shopping mall, is composed of training and apply process. The training process is designed to make the base brand network (BBN) using historical transaction data. Then, the scheme yields recommended brands for shopping customers based on their behaviors and BBN in the apply process. In order to verify the performance of the proposed scheme, simulation was conducted using purchase history data from a department store in Korea. Then, the results was compared to the previous scheme. Experimental results showd that the proposed scheme performs brand recommendation effectively in off-line shopping mall.

• Journal of architectural history
• /
• v.22 no.5
• /
• pp.37-46
• /
• 2013

This paper aims to examine the constructional background and process of the Japanese military installations of Jisim-do, especially based on the military secret documents. Furthermore, it aims to analyze the characteristics of the remains. First, the study looked into the procedure of forcible occupation by Japan, involving the background of the designation and forcible accommodation of military reservations, and forced eviction by the purchase of land. Second, the study identified the background of construction, purpose, and construction period of each battery built throughout the 'Fort maintenance period' according to changes in international situations. Third, it is the 'Chukseongbu' that supervised the construction of fortresses. Fourth, the study considered a series of arrangement processes in which Jisim-do became a fortresses through "Yukgunsungdae-ilgi", a military operations report for the Japanese army. Through this, it discovered a clear construction process, construction details, and the supply for Jisim-do. The study was also able to reveal the meticulousness in constructing firm facilities more promptly from the 'design tactics'.

• Journal of Information Technology Applications and Management
• /
• v.20 no.3_spc
• /
• pp.219-230
• /
• 2013

Real time accessiblity and agility in Ubiquitous-commerce is required under ubiquitous computing environment. The Research has been actively processed in e-commerce so as to improve the accuracy of recommendation. Existing Collaborative filtering (CF) can not reflect contents of the items and has the problem of the process of selection in the neighborhood user group and the problems of sparsity and scalability as well. Although a system has been practically used to improve these defects, it still does not reflect attributes of the item. In this paper, to solve this problem, We can use a implicit method which is used by customer's data and purchase history data. We propose a new clustering method of weighted preference for customer using k-means clustering and Bayesian network in order to improve the accuracy of recommendation. To verify improved performance of the proposed system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• Journal of Korean Institute of Industrial Engineers
• /
• v.41 no.1
• /
• pp.10-16
• /
• 2015

In this study, we suggest a method to predict probability distribution of a new customer's degree of loyalty using C-CRF that reflects the RFM score and similarity to the neighbors of the customer. An RFM score prediction model is introduced to construct the first feature function of C-CRF. Integrating demographical similarity, purchasing characteristic similarity and purchase history similarity, we make a unified similarity variable to configure the second feature function of C-CRF. Then parameters of each feature function are estimated and we train our C-CRF model by training data set and suggest a probabilistic distribution to estimate a new customer's degree of loyalty. An example is provided to illustrate our model.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.7
• /
• pp.9-16
• /
• 2016

Collaborative filtering(CF) uses the purchase or item rating history of other users, but does not need additional properties or attributes of users and items. Hence CF is known th be the most successful recommendation technology. But conventional CF approach has some significant weakness, such as the new user problem. In this paper, we propose a approach using word embedding with skip-gram for learning distributed item representations. In particular, we show that this approach can be used to capture precise item for solving the "new user problem." The proposed approach has been tested on the Movielens databases. We compare the performance of the user based CF, item based CF and our approach by observing the change of recommendation results according to the different number of item rating information. The experimental results shows the improvement in our approach in measuring the precision applied to new user problem situations.

• International Journal of Highway Engineering
• /
• v.14 no.5
• /
• pp.157-164
• /
• 2012

PURPOSES: Regional offices of the Ministry of Land, Transport and Maritime Affairs use a computerized system called KAMIS so as to manage road equipment systematically. Road agencies can record number of operating days by equipment, actual working hours, accumulated operating hours (or distance) by equipment, and operating cost. However, KAMIS does not provide critical information, although it is strongly related to efficient road management equipment operation. In other words, road agencies do not know whether they have sufficient equipment to handle their actual work. METHODS: Therefore, this study suggests a methodology to evaluate for operational efficiency of road management equipment using analytical hierarchy process(AHP). First of all, estimated weights related criteria can be produced by AHP, and then use operational history by pieces of equipment. RESULTS: Results show that importance of management work can differ from weather conditions through five areas. CONCLUSIONS: Commonly, this results can imply to help save money for the purchase and maintenance of road management equipment, and they would improve the functional performance of KAMIS.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2002.05a
• /
• pp.93-97
• /
• 2002

In this paper, we propose personalized recommendation techniques based on multidimensional scaling (MDS) method for Business to Consumer Electronic Commerce. The multidimensional scaling method is traditionally used in marketing domain for analyzing customers' perceptional differences about brands and products. In this study, using purchase history data, customers in learning dataset are assigned to specific product categories, and after then using MDS a positioning map is generated to map product categories and alternative advertisements. The positioning map will be used to select personalized advertisement in real time situation. In this paper, we suggest the detail design of personalized recommendation method using MDS and compare with other approaches (random approach, collaborative filtering, and TOP3 approach)

• Asia pacific journal of information systems
• /
• v.9 no.4
• /
• pp.107-124
• /
• 1999

This paper describes a personalized advertisement technique as a part of intelligent customer services in Internet shopping malls. Based on customers' initial profile, purchase history, and behaviors in an Internet shopping mall, the technique displays appropriate advertisements on Internet web pages when customers' visit to the shopping mall. Customers preference scores for product groups which are main sources to select advertisements, are stored either a preference table or preference trees. Both of the two storage methods can support selection of advertisements on real time, and the preference tree method can reflect affinity among product groups. The suggested technique selects different advertisements to reflect changes of customers preferences as time goes by. An experiment has been performed to evaluate the effectiveness of the algorithm, which revealed that the algorithm selects more customer-oriented advertisements rather than random selection.

• Journal of Internet Computing and Services
• /
• v.21 no.2
• /
• pp.65-72
• /
• 2020

In this paper, a USB module with fingerprint recognition was designed as a distributed node of blockchain on distributed ID (DID, distributed ID) for user identification. This biometric-linked fingerprint recognition device was verified for the real-time authentication process of authentication transaction with FIDO(Fast IDentity Online) server. Blockchain DID-based services were proposed like as a method of individual TV rating survey, and recommending service for customized shopping channels, and crypto-currency, too. This DID based remote service can be improved by recognizing of channel-changing information through personal identification. The proposed information of production purchase can be shared by blockchain. And customized service can be provided for the utilization of purchase history in shoppingmall using distributed ID. As a result, this blockchain node-device and Samsung S10 Key-srore with FIDO service can be certified for additional transactions through various biometric authentication like fingerprint, and face recognition.

• Management & Information Systems Review
• /
• v.39 no.2
• /
• pp.113-126
• /
• 2020

This study suggested implications by dividing the concept of brand origin into national image and manufacturing capacity image, verifying the direct impact of these variables on brand trust and brand loyalty, and verifying the difference between products with the effect on brand trust of brand origin, which is the result of verification. The specific implications of this paper are as follows. First, brand origin does not directly affect brand loyalty, but it can have a direct impact on the preceding variable, brand loyalty. This study may conclude that it is desirable to define the factors that affect the purchase selection indirectly through the assessment of product properties or positive effects on brand image rather than having a direct impact on product purchase or selection. Second, the difference in brand origin influence by product characteristics was very evident. Past studies were limited to a few products, so pan-product testing was not conducted, and the empirical power was judged to be limited, so this study included a variety of products and tried to detect differences between products through actual empirical research. Involvement and self-congruity have been presented with results that can be judged as important variables for brand origin to affect brand performance and variables. Looking at the role of the brand origin for each product characteristic by distinguishing between product characteristics and whether or not products related to quality, history, authenticity, etc., the product recognized as high quality and the product recognized as having high integrity showed higher effect of the brand origin, but history was a product characteristic that did not show the effect of the brand origin.