• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.19-45
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• 2008

This study is to empirically examine the primary dimensions of visual merchandising (VMD) of internet shopping mall, namely store design, merchandise, and merchandising cues, to be a attractive virtual store to the shoppers. The authors reviewed the literature related to the major components of VMD from the perspective of the AIDA model, which has been mainly applied to the offline store settings. The major purposes of the study are as follows; first, tries to derive the variables related with the components of visual merchandising through reviewing the existing literatures, establish the hypotheses, and test it empirically. Second, examines the relationships between the components of VMD and the attitude toward the VMD, however, putting more emphasis on finding out the component structure of the VMD. VMD needs to be examined with the perspective that an online shopping mall is a virtual self-service or clerkless store, which could reduce the number of employees, help the shoppers search, evaluate and purchase for themselves, and to be explored in terms of the in-store persuasion processes of customers. This study reviewed the literatures related to store design, merchandise, and merchandising cues which might be relevant to the store, product, and promotion respectively. VMD is a total communication tool, and AIDA model could explain the in-store consumer behavior of online shopping. Store design has to do with triggering a consumer attention to the online mall, merchandise with a product related interest, and merchandising cues with promotions such as recommendation and links that induce the desire to pruchase. These three steps might be seen as the processes for purchase actions. The theoretical rationale for the relationship between VMD and AIDA could be found in Tyagi(2005) that the three steps of consumer-oriented merchandising are a store, a product assortment, and placement, in Omar(1999) that three types of interior display are a architectural design display, commodity display, and point-of-sales(POS) display, and in Davies and Ward(2005) that the retail store interior image is related to an atmosphere, merchandise, and in-store promotion. Lee et al(2000) suggested as the web merchandising components a merchandising cues, a shopping metaphor which is an assistant tool for search, a store design, a layout(web design), and a product assortment. The store design which includes differentiation, simplicity and navigation is supposed to be related to the attention to the virtual store. Second, the merchandise dimensions comprising product assortments, visual information and product reputation have to do with the interest in the product offerings. Finally, the merchandising cues that refer to merchandiser(MD)'s recommendation of products and providing the hyperlinks to relevant goods for the shopper is concerned with attempt to induce the desire to purchase. The questionnaire survey was carried out to collect the data about the consumers who would shop at internet shopping malls frequently. To select the subject malls, the mall ranking data announced by a mall rating agency was used to differentiate the most popular and least popular five mall each. The subjects was instructed to answer the questions after navigating the designated mall for five minutes. The 300 questionnaire was distributed to the consumers, 166 samples were used in the final analysis. The empirical testing focused on identifying and confirming the dimensionality of VMD and its subdimensions using a structural equation modeling method. The confirmatory factor analysis for the endogeneous and exogeneous variables was carried out in four parts. The second-order factor analysis was done for a store design, a merchandise, and a merchandising cues, and first-order confirmatory factor analysis for the attitude toward the VMD. The model test results shows that the chi-square value of structural equation is 144.39(d.f 49), significant at 0.01 level which means the proposed model was rejected. But, judging from the ratio of chi-square value vs. degree of freedom, the ratio was 2.94 which smaller than an acceptable level of 3.0, RMR is 0.087 which is higher than a generally acceptable level of 0.08. GFI and AGFI is turned out to be 0.90 and 0.84 respectively. Both NFI and NNFI is 0.94, and CFI 0.95. The major test results are as follows; first, the second-order factor analysis and structural equational modeling reveals that the differentiation, simplicity and ease of identifying current status of the transaction are confirmed to be subdimensions of store design and to be a significant predictors of the dependent variable. This result implies that when designing an online shopping mall, it is necessary to differentiate visually from other malls to improve the effectiveness of the communications of store design. That is, the differentiated store design raise the contrast stimulus to sensory organs to promote the memory of the store and to have a favorable attitude toward the VMD of a store. The results that navigation which means the easiness of identifying current status of shopping affects the attitude to VMD could be interpreted that the navigating processes via the hyperlinks which is characteristics of an internet shopping is a complex and cognitive process and shoppers are likely to lack the sense of overall structure of the store. Consequently, shoppers are likely to be alost amid shopping not knowing where to go. The orientation tool enhance the accessibility of information to raise the perceptive power about the store environment.(Titus & Everett 1995) Second, the primary dimension of merchandise and its subdimensions was confirmed to be unidimensional respectively, have a construct validity, and nomological validity which the VMD dimensions supposed to have a positive correlation with the dependent variable. The subdimensions of product assortment, brand fame and information provision proved to have a positive effect on the attitude toward the VMD. It could be interpreted that the more plentiful the product and brand assortment of the mall is, the more likely the shoppers to favor it. Brand fame and information provision as well affect the VMD attitude, which means that the more famous the brand, the more likely the shoppers would trust and feel familiar with the mall, and the plentifully and visually presented information could have the shopper have a favorable attitude toward the store VMD. Third, it turned out to be that merchandising cue of product recommendation and hyperlinks affect the VMD attitude. This could be interpreted that recommended products could reduce the uncertainty related with the purchase decision, and the hyperlinks to relevant products would help the shopper save the cognitive effort exerted into the information search and gathering, which could lead to a favorable attitude to the VMD. This study tried to sheds some new light on the VMD of online store by reviewing the variables mentioned to be relevant with offline VMD in the existing literatures, and tried to link the VMD components from the perspective of AIDA model. The effect size of the VMD dimensions on the attitude was in the order of the merchandise, the store design and the merchandising cues.It is said that an internet has an unlimited place for display, however, the virtual store is not unlimited since the consumer has a limited amount of cognitive ability to process the external information and internal memory. Particularly, the shoppers are likely to face some difficulties in decision making on account of too many alternative and information overloads. Therefore, the internet shopping mall manager should take into consideration the cost of information search on the part of the consumer, to establish the optimal product placements and search routes. An efficient store composition would be possible by reducing the psychological burdens and cognitive efforts exerted to information search and alternatives evaluation. The store image is in most part determined by the product category and its brand it deals in. The results of this study support this proposition that the merchandise is most important to the VMD attitude than other components, the manager is required to take a strategic approach to VMD. The internet users are getting more accustomed and more knowledgeable about the internet media and more likely to accept the internet as a shopping channel as the period of time during which they use the internet to shop become longer. The web merchandiser should be aware that the product introduction using a moving pictures and a bulletin board become more important in order to present the interactive product information visually and communicate with customers more actively, therefore leading to making the quantity and quality of product information more rich.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.167-181
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• 2018

Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN(Convolutional Neural Network), which is known as the effective solution for recognizing and classifying images or voices, has been popularly applied to classification and prediction problems. In this study, we investigate the way to apply CNN in business problem solving. Specifically, this study propose to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. As mentioned, CNN has strength in interpreting images. Thus, the model proposed in this study adopts CNN as the binary classifier that predicts stock market direction (upward or downward) by using time series graphs as its inputs. That is, our proposal is to build a machine learning algorithm that mimics an experts called 'technical analysts' who examine the graph of past price movement, and predict future financial price movements. Our proposed model named 'CNN-FG(Convolutional Neural Network using Fluctuation Graph)' consists of five steps. In the first step, it divides the dataset into the intervals of 5 days. And then, it creates time series graphs for the divided dataset in step 2. The size of the image in which the graph is drawn is $40(pixels){\times}40(pixels)$, and the graph of each independent variable was drawn using different colors. In step 3, the model converts the images into the matrices. Each image is converted into the combination of three matrices in order to express the value of the color using R(red), G(green), and B(blue) scale. In the next step, it splits the dataset of the graph images into training and validation datasets. We used 80% of the total dataset as the training dataset, and the remaining 20% as the validation dataset. And then, CNN classifiers are trained using the images of training dataset in the final step. Regarding the parameters of CNN-FG, we adopted two convolution filters ($5{\times}5{\times}6$ and $5{\times}5{\times}9$) in the convolution layer. In the pooling layer, $2{\times}2$ max pooling filter was used. The numbers of the nodes in two hidden layers were set to, respectively, 900 and 32, and the number of the nodes in the output layer was set to 2(one is for the prediction of upward trend, and the other one is for downward trend). Activation functions for the convolution layer and the hidden layer were set to ReLU(Rectified Linear Unit), and one for the output layer set to Softmax function. To validate our model - CNN-FG, we applied it to the prediction of KOSPI200 for 2,026 days in eight years (from 2009 to 2016). To match the proportions of the two groups in the independent variable (i.e. tomorrow's stock market movement), we selected 1,950 samples by applying random sampling. Finally, we built the training dataset using 80% of the total dataset (1,560 samples), and the validation dataset using 20% (390 samples). The dependent variables of the experimental dataset included twelve technical indicators popularly been used in the previous studies. They include Stochastic %K, Stochastic %D, Momentum, ROC(rate of change), LW %R(Larry William's %R), A/D oscillator(accumulation/distribution oscillator), OSCP(price oscillator), CCI(commodity channel index), and so on. To confirm the superiority of CNN-FG, we compared its prediction accuracy with the ones of other classification models. Experimental results showed that CNN-FG outperforms LOGIT(logistic regression), ANN(artificial neural network), and SVM(support vector machine) with the statistical significance. These empirical results imply that converting time series business data into graphs and building CNN-based classification models using these graphs can be effective from the perspective of prediction accuracy. Thus, this paper sheds a light on how to apply deep learning techniques to the domain of business problem solving.

• Journal of Haehwa Medicine
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• v.8 no.2
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• pp.211-243
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• 2000

This study was performed to investigate the cause, symptom, treatment, medicine of Wei symptom through the literature of oriental and western medicine. The results obtained were as follows: 1. Wei symptom is the symptom that reveals muscle relaxation without contraction and muscle relaxation occures in the lower limb or upper limb, in severe case, leads to death. 2. Since the pathology and etiology of Wei symptom was first described as "pe-yeol-yeop-cho"(肺熱葉焦) in Hung Ti Nei Ching(黃帝內經), for generations most doctors had have accepted it. but after Dan Ge(丹溪), it had been classified into seven causes, damp-heat(濕熱), phlegm-damp(濕痰), deficiency of qi(氣虛), deficiency of blood(血虛), deficiency of yin(陰處), stagnant blood(死血), stagnant food(食積). Chang Gyeng Ag(張景岳) added the cause of deficiency of source qi(元氣). 3. The concept of "To treat Yangming, most of all"(獨治陽明) was emphasized in the treatment of Wei symptom and contains nourishment of middle warmer energy(補益中氣), clearance of yangming-damp-heat(淸化陽明濕熱). 4. Since Nei-ching era(內經時代), Wei and Bi symptom(痺症) is differenciated according to the existence of pain. After Ming era(明代) appeared theory of co-existence of Wei symptom and pain or numbness but they were accepted as a sign of Wei symptom caused by the pathological factor phelgm(痰), damp(濕), stagnancy(瘀). 5. In the western medical point of view, Wei symptom is like paraplegia, or tetraplegia. and according to the causative disease, it is accompanied by dysesthesia, paresthsia, pain. thus it is more recommended to use hwal-hyel-hwa-ae(活血化瘀) method considering damp-heat(濕熱), qi deficiency of spleen and stornach(脾胃氣虛) as pathological basis than to simply differenciate Wei and Bi symptom according to the existence of pain. 6. The cause of Gullian-Barre syndrome(GBS) is consist of two factors, internal and external. Internal factors include asthenia of spleen and stomach, and of liver and kidney. External factors include summur-damp(暑濕), damp-heat(濕熱), cold-damp(寒濕) and on the basis of "classification and treatment according to the symptom of Zang-Fu"(臟腑辨證論治), the cause of GBS is classified into injury of body fluid by lung heat(肺熱傷津), infiltration of damp-heat(濕熱浸淫), asthenia of spleen and kidney(脾腎兩虛), asthenia of spleen and stomach(脾胃虛弱), asthenia of liver and kidney (肝腎兩虛). 7. The cause of GBS is divided by according to the disease developing stage: Early stage include dryness-heat(燥熱), damp(濕邪), phlegm(痰濁), stagnant blood(瘀血), and major treatment is reducing of excess(瀉實). Late stage include deficiency of essence(精虛), deficiency with excess(虛中挾實), and essencial deficiency of liver and kidney(肝腎精不足) is major point of treatment. 8. Following is the herbal medicine of GBS according to the stage. In case of summur-damp(暑濕), chung-seu-iki-tang(淸暑益氣湯) is used which helps cooling and drainage of summer-damp(淸利暑濕), reinforcement of qi and passage of collateral channels(補氣通絡). In case of damp-heat, used kun-bo-hwan(健步丸), In case of cool-damp(寒濕), used 'Mahwang-buja-sesin-tang with sam-chul-tang'(麻黃附子細辛湯合蓼朮湯). In case of asthenia of spleen and kidney, used 'Sam-lyeng-baik-chul san'(蔘笭白朮散), In case of asthenia of liver and kidney, used 'Hojam-hwan'(虎潛丸). 9. Following is the herbal medicine of GBS according to the "classification and treatment according to the symptom of Zang-Fu"(臟腑辨證論治). In the case of injury of body fluid by lung heat(肺熱傷津), 'Chung-jo-gu-pae-tang'(淸燥救肺湯) is used. In case of 'infiltration of damp-heat'(濕熱浸淫), us-ed 'Yi-myo-hwan'(二妙丸), In case of 'infiltration of cool-damp'(寒濕浸淫), us-ed 'Yui-lyung-tang', In case of asthenia of spleen, used 'Sam-lyung-bak-chul-san'. In case of yin-deficiency of liver and kidney(肝腎陰虛), used 'Ji-bak-ji-hwang-hwan'(知柏地黃丸), or 'Ho-jam-hwan'(虎潛丸). 10. Cervical spondylosis with myelopathy is occuered by compression or ischemia of spinal cord. 11. The cause of cervical spondylosis with myelopathy consist of 'flow disturbance of the channel points of tai-yang'(太陽經兪不利), 'stagnancy of cool-damp'(寒濕凝聚), 'congestion of phlegm-damp stagnant substances'(痰濕膠阻), 'impairment of liver and kidney'(肝腎虛損). 12. In treatment of cervical spondylosis with myelopathy, are used 'Ge-ji-ga-gal-geun-tang-gagam'(桂枝加葛根湯加減), 'So-hwal-lack-dan-hap-do-hong-eum-gagam(小活絡丹合桃紅飮加減), 'Sin-tong-chuck-ue-tang-gagam(身痛逐瘀湯加減), 'Do-dam-tang-hap-sa-mul-tang-gagam'(導痰湯合四物湯加減), 'Ik-sin-yang-hyel-guen-bo-tang'(益腎養血健步湯加減), 'Nok-gakyo-hwan-gagam'(鹿角膠丸加減). 13. The cause of muscle dystropy is related with 'the impairement of vital qi'(元氣損傷), and 'impairement of five Zang organ'(五臟敗傷). Symptoms and signs are classified into asthenia of spleen and stomach, deficiency with excess, 'deficiency of liver and kidney'(肝腎不足) infiltration of damp-heat, 'deficiency of qi and blood'(氣血兩虛), 'yang deficiency of spleen and kidney'(脾腎陽虛). 14. 'Bo-jung-ik-gi-tang'(補中益氣湯), 'Gum-gang-hwan'(金剛丸), 'Yi-gong-san-hap-sam-myo-hwan'(異功散合三妙丸), 'Ja-hyel-yang-gun-tang'(滋血養筋湯), 'Ho-jam-hwan'(虎潛丸) are used for muscle dystropy. 15. The causes of myasthenia gravis are classified into 'insufficiency of middle warmer energy'(中氣不足), 'deficiency of qi and yin of spleen and kidney'(脾腎兩處), 'asthenia of qi of spleen'(脾氣虛弱), 'deficiency of qi and blood'(氣血兩虛), 'yang deficiency of spleen and kidney'(脾腎陽虛). 16. 'Bo-jung-ik-gi-tang-gagam'(補中益氣湯加減), 'Sa-gun-ja-tang-hap-gi-guk-yang-hyel-tang'(四君子湯合杞菊地黃湯), 'Sa-gun-ja-tang-hap-u-gyi-eum-gagam'(四君子湯合右歸飮加減), 'Pal-jin-tang'(八珍湯), 'U-gyi-eum'(右歸飮) are used for myasthenia gravis.

• Magazine of the Korean Society of Agricultural Engineers
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• v.17 no.1
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• pp.3642-3654
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• 1975

The purpose of this thesis is to derive a unit hydrograph which may be applied to the ungaged watershed area from the relations between directly measurable unitgraph properties such as peak discharge(qp), time to peak discharge (Tp), and lag time (Lg) and watershed characteristics such as river length(L) from the given station to the upstream limits of the watershed area in km, river length from station to centroid of gravity of the watershed area in km (Lca), and main stream slope in meter per km (S). Other procedure based on routing a time-area diagram through catchment storage named Instantaneous Unit Hydrograph(IUH). Dimensionless unitgraph also analysed in brief. The basic data (1969 to 1973) used in these studies are 9 recording level gages and rating curves, 41 rain gages and pluviographs, and 40 observed unitgraphs through the 9 sub watersheds in Nak Oong River basin. The results summarized in these studies are as follows; 1. Time in hour from start of rise to peak rate (Tp) generally occured at the position of 0.3Tb (time base of hydrograph) with some indication of higher values for larger watershed. The base flow is comparelatively higher than the other small watershed area. 2. Te losses from rainfall were divided into initial loss and continuing loss. Initial loss may be defined as that portion of storm rainfall which is intercepted by vegetation, held in deppression storage or infiltrated at a high rate early in the storm and continuing loss is defined as the loss which continues at a constant rate throughout the duration of the storm after the initial loss has been satisfied. Tis continuing loss approximates the nearly constant rate of infiltration (${\Phi}$-index method). The loss rate from this analysis was estimated 50 Per cent to the rainfall excess approximately during the surface runoff occured. 3. Stream slope seems approximate, as is usual, to consider the mainstreamonly, not giving any specific consideration to tributary. It is desirable to develop a single measure of slope that is representative of the who1e stream. The mean slope of channel increment in 1 meter per 200 meters and 1 meter per 1400 meters were defined at Gazang and Jindong respectively. It is considered that the slopes are low slightly in the light of other river studies. Flood concentration rate might slightly be low in the Nak Dong river basin. 4. It found that the watershed lag (Lg, hrs) could be expressed by Lg=0.253 (L.Lca)0.4171 The product L.Lca is a measure of the size and shape of the watershed. For the logarithms, the correlation coefficient for Lg was 0.97 which defined that Lg is closely related with the watershed characteristics, L and Lca. 5. Expression for basin might be expected to take form containing theslope as {{{{ { L}_{g }=0.545 {( { L. { L}_{ca } } over { SQRT {s} } ) }^{0.346 } }}}} For the logarithms, the correlation coefficient for Lg was 0.97 which defined that Lg is closely related with the basin characteristics too. It should be needed to take care of analysis which relating to the mean slopes 6. Peak discharge per unit area of unitgraph for standard duration tr, ㎥/sec/$\textrm{km}^2$, was given by qp=10-0.52-0.0184Lg with a indication of lower values for watershed contrary to the higher lag time. For the logarithms, the correlation coefficient qp was 0.998 which defined high sign ificance. The peak discharge of the unitgraph for an area could therefore be expected to take the from Qp=qp. A(㎥/sec). 7. Using the unitgraph parameter Lg, the base length of the unitgraph, in days, was adopted as {{{{ {T}_{b } =0.73+2.073( { { L}_{g } } over {24 } )}}}} with high significant correlation coefficient, 0.92. The constant of the above equation are fixed by the procedure used to separate base flow from direct runoff. 8. The width W75 of the unitgraph at discharge equal to 75 per cent of the peak discharge, in hours and the width W50 at discharge equal to 50 Per cent of the peak discharge in hours, can be estimated from {{{{ { W}_{75 }= { 1.61} over { { q}_{b } ^{1.05 } } }}}} and {{{{ { W}_{50 }= { 2.5} over { { q}_{b } ^{1.05 } } }}}} respectively. This provides supplementary guide for sketching the unitgraph. 9. Above equations define the three factors necessary to construct the unitgraph for duration tr. For the duration tR, the lag is LgR=Lg+0.2(tR-tr) and this modified lag, LgRis used in qp and Tb It the tr happens to be equal to or close to tR, further assume qpR=qp. 10. Triangular hydrograph is a dimensionless unitgraph prepared from the 40 unitgraphs. The equation is shown as {{{{ { q}_{p } = { K.A.Q} over { { T}_{p } } }}}} or {{{{ { q}_{p } = { 0.21A.Q} over { { T}_{p } } }}}} The constant 0.21 is defined to Nak Dong River basin. 11. The base length of the time-area diagram for the IUH routing is {{{{C=0.9 {( { L. { L}_{ca } } over { SQRT { s} } ) }^{1/3 } }}}}. Correlation coefficient for C was 0.983 which defined a high significance. The base length of the T-AD was set to equal the time from the midpoint of rain fall excess to the point of contraflexure. The constant K, derived in this studies is K=8.32+0.0213 {{{{ { L} over { SQRT { s} } }}}} with correlation coefficient, 0.964. 12. In the light of the results analysed in these studies, average errors in the peak discharge of the Synthetic unitgraph, Triangular unitgraph, and IUH were estimated as 2.2, 7.7 and 6.4 per cent respectively to the peak of observed average unitgraph. Each ordinate of the Synthetic unitgraph was approached closely to the observed one.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.