• 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.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.1-29
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• 2007

The flow theory becomes one of the most important frameworks in the internet research arena. Hoffman and Novak proposed a hierarchical flow model showing the antecedents and outcomes of flow and the relationship among these variables in the hyper-media computer circumstances (Hoffman and Novak 1996). This model was further tested after their initial research (Novak, Hoffman, and Yung 2000). At their paper, Hoffman and Novak explained that the balance of challenge and skill leads to flow which means the positive optimal state of mind (Hoffman and Novak 1996). An imbalance between challenge and skill, leads to negative states of mind like anxiety, boredom, apathy (Csikszentmihalyi and Csikszentmihalyi 1988). Almost all research on the flow 4-channel model have been focusingon flow, the positive state of mind (Ellis, Voelkl, and Morris 1994 Mathwick and Rigdon 2004). However, it also needs to examine the formation of the negative states of minds and their outcomes. Flow researchers explain play or playfulness as antecedents or the early state of flow. However, play has been regarded as a distinct concept from flow in the flow literatures (Hoffman and Novak 1996; Novak, Hoffman, and Yung 2000). Mathwick and Rigdon discovered the influences of challenge and skill on play; they also observed the influence of play on web-loyalty and brand loyalty (Mathwick and Rigdon 2004). Unfortunately, they did not go so far as to test the influences of play on state of mind. This study focuses on the relationships between state of mind in the flow 4-channel model and play. Early research has attempted to hypothetically explain state of mind in flow theory, but has not been tested except flow until now. Also the importance of play has been emphasized in the flow theory, but has not been tested in the flow 4-channel model context. This researcher attempts to analyze the relationships among state of mind, skill of play, challenge, state of mind and web loyalty. For this objective, I developed a measure for state of mind and defined the concept of play as a trait. Then, the influences of challenge and skill on the state of mind and play under on-line shopping conditions were tested. Also the influences of play on state of mind were tested and those of flow and play on web loyalty were highlighted. 294 undergraduate students participated in this research survey. They were asked to respond about their perceptions of challenge, skill, state of mind, play, and web-loyalty to on-line shopping mall. Respondents were restricted to students who bought products on-line in a month. In case of buying products at two or more on-line shopping malls, they asked to respond about the shopping mall where they bought the most important one. Construct validity, discriminant validity, and convergent validity were used to check the measurement validations. Also, Cronbach's alpha was used to check scale reliability. A series of exploratory factor analyses was conducted. This researcher conducted confirmatory factor analyses to assess the validity of measurements. All items loaded significantly on their respective constructs. Also, all reliabilities were greater than.70. Chi-square difference tests and goodness of fit tests supported discriminant and convergent validity. The results of clustering and ANOVA showed that high challenge and high skill leaded to flow, low challenge and high skill leaded to boredom, and low challenge and low skill leaded to apathy. But, it was different from my expectation that high challenge and low skill didnot lead to anxiety but leaded to apathy. The results also showed that high challenge and high skill, and high challenge and low skill leaded to the highest play. Low challenge leaded to low play. 4 Structural Equation Models were built by flow, anxiety, boredom, apathy for analyzing not only the impact of play on state of mind and web-loyalty, but also that of state of mind on web-loyalty. According the analyses results of these models, play impacted flow and web-loyalty positively, but impacted anxiety, boredom, and apathy negatively. Results also showed that flow impacted web-loyalty positively, but anxiety, boredom, and apathy impacted web-loyalty negatively. The interpretations and implications of the test results of the hypotheses are as follows. First, respondents belonging to different clusters based on challenge and skill level experienced different states of mind such as flow, anxiety, boredom, apathy. The low challenge and low skill group felt the highest anxiety and apathy. It could be interpreted that this group feeling high anxiety or fear, then avoided attempts to shop on-line. Second, it was found that higher challenge leads to higher levels of play. Test results show that the play level of the high challenge and low skill group (anxiety group) was higher than that of the high challenge and high skill group (flow group). However, this was not significant. Third, play positively impacted flow and negatively impacted boredom. The negative impacts on anxiety and apathy were not significant. This means that the combination of challenge and skill creates different results. Forth, play and flow positively impacted web-loyalty, but anxiety, boredom, apathy had negative impacts. The effect of play on web-loyalty was stronger in case of anxiety, boredom, apathy group than fl ow group. These results show that challenge and skill influences state of mind and play. Results also demonstrate how play and flow influence web-loyalty. It implies that state of mind and play should be the core marketing variables in internet marketing. The flow theory has been focusing on flow and on the positive outcomes of flow experiences. But, this research shows that lots of consumers experience the negative state of mind rather than flow state in the internet shopping circumstance. Results show that the negative state of mind leads to low or negative web-loyalty. Play can have an important role with the web-loyalty when consumers have the negative state of mind. Results of structural equation model analyses show that play influences web-loyalty positively, even though consumers may be in the negative state of mind. This research found the impacts of challenge and skill on state of mind in the flow 4-channel model, not only flow but also anxiety, boredom, apathy. Also, it highlighted the role of play in the flow 4-channel model context and impacts on web-loyalty. However, tests show a few different results from hypothetical expectations such as the highest anxiety level of apathy group and insignificant impacts of play on anxiety and apathy. Further research needs to replicate this research and/or to compare 3-channel model with 4-channel model.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.1-25
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• 2008

Ⅰ. Introduction Retailers in the 21st century are being told that future retailers are those who can execute seamless multi-channel access. The reason is that retailers should be where shoppers want them, when they want them anytime, anywhere and in multiple formats. Multi-channel access is considered one of the top 10 trends of all business in the next decade (Patricia T. Warrington, et al., 2007) And most firms use both direct and indirect channels in their markets. Given this trend, we need to evaluate a channel equity more systematically than before as this issue is expected to get more attention to consumers as well as to brand managers. Consumers are becoming very much confused concerning the choice of place where they shop for durable goods as there are at least 6-7 retail options. On the other hand, manufacturers have to deal with category killers, their dealers network, Internet shopping malls, and other avenue of distribution channels and they hope their retail channel behave like extensions of their own companies. They would like their products to be foremost in the retailer's mind-the first to be proposed and effectively communicated to potential customers. To enable this hope to come reality, they should know each channel's advantages and disadvantages from consumer perspectives. In addition, customer satisfaction is the key determinant of retail customer loyalty. However, there are only a few researches regarding the effects of shopping satisfaction and perceptions on consumers' channel choices and channels. The purpose of this study was to assess Korean consumers' channel choice and satisfaction towards channels they prefer to use in the case of electronic goods shopping. Korean electronic goods retail market is one of good example of multi-channel shopping environments. As the Korea retail market has been undergoing significant structural changes since it had opened to global retailers in 1996, new formats such as hypermarkets, Internet shopping malls and category killers have arrived for the last decade. Korean electronic goods shoppers have seven major channels : (1)category killers (2) hypermarket (3) manufacturer dealer shop (4) Internet shopping malls (5) department store (6) TV home-shopping (7) speciality shopping arcade. Korean retail sector has been modernized with amazing speed for the last decade. Overall summary of major retail channels is as follows: Hypermarket has been number 1 retailer type in sales volume from 2003 ; non-store retailing has been number 2 from 2007 ; department store is now number 3 ; small scale category killers are growing rapidly in the area of electronics and office products in particular. We try to evaluate each channel's equity using a consumer survey. The survey was done by telephone interview with 1000 housewife who lives nationwide. Sampling was done according to 2005 national census and average interview time was 10 to 15 minutes. Ⅱ. Research Summary We have found that seven major retail channels compete with each other within Korean consumers' minds in terms of price and service. Each channel seem to have its unique selling points. Department stores were perceived as the best electronic goods shopping destinations due to after service. Internet shopping malls were perceived as the convenient channel owing to price checking. Category killers and hypermarkets were more attractive in both price merits and location conveniences. On the other hand, manufacturers dealer networks were pulling customers mainly by location and after service. Category killers and hypermarkets were most beloved retail channel for Korean consumers. However category killers compete mainly with department stores and shopping arcades while hypermarkets tend to compete with Internet and TV home shopping channels. Regarding channel satisfaction, the top 3 channels were service-driven retailers: department stores (4.27); dealer shop (4.21); and Internet shopping malls (4.21). Speciality shopping arcade(3.98) were the least satisfied channels among Korean consumers. Ⅲ. Implications We try to identify the whole picture of multi-channel retail shopping environments and its implications in the context of Korean electronic goods. From manufacturers' perspectives, multi-channel may cause channel conflicts. Furthermore, inter-channel competition draws much more attention as hypermarkets and category killers have grown rapidly in recent years. At the same time, from consumers' perspectives, 'buy where' is becoming an important buying decision as it would decide the level of shopping satisfaction. We need to develop the concept of 'channel equity' to manage multi-channel distribution effectively. Firms should measure and monitor their prime channel equity in regular basis to maximize their channel potentials. Prototype channel equity positioning map has been developed as follows. We expect more studies to develop the concept of 'channel equity' in the future.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.195-215
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• 2008

The scarcity is pervasive aspect of human life and is a fundamental precondition of economic behavior of consumers. Also, the effect of scarcity message is a power social influence principle used by marketers to increase the subjective desirability of products. Because valuable objects are often scare, consumers tend to infer the scarce objects are valuable. Marketers often do base promotional appeals on the principle of scarcity to increase the subjective desirability their products among consumers. Specially, advertisers and retailers often promote their products using restrictions. These restriction act to constraint consumers' ability th take advantage of the promotion and can assume several forms. For example, some promotions are advertised as limited time offers, while others limit the quantity that can be bought at the deal price by employing the statements such as 'limit one per consumer,' 'limit 5 per customer,' 'limited products for special commemoration celebration,' Some retailers use statements extensively. A recent weekly flyer by a prominent retailer limited purchase quantities on 50% of the specials advertised on front page. When consumers saw these phrase, they often infer value from the product that has limited availability or is promoted as being scarce. But, the past researchers explored a direct relationship between the purchase quantity and time limit on deal purchase intention. They also don't explored that all restriction message are not created equal. Namely, we thought that different restrictions signal deal value in different ways or different mechanism. Consumers appear to perceive that time limits are used to attract consumers to the brand, while quantity limits are necessary to reduce stockpiling. This suggests other possible differences across restrictions. For example, quantity limits could imply product quality (i.e., this product at this price is so good that purchases must be limited). In contrast, purchase preconditions force the consumer to spend a certain amount to qualify for the deal, which suggests that inferences about the absolute quality of the promoted item would decline from purchase limits (highest quality) to time limits to purchase preconditions (lowest quality). This might be expected to be particularly true for unfamiliar brands. However, a critical but elusive issue in scarcity message research is the impacts of a inferred motives on the promoted scarcity message. The past researchers not explored possibility of inferred motives on the scarcity message context. Despite various type to the quantity limits message, they didn't separated scarcity message among the quantity limits. Therefore, we apply a stricter definition of scarcity message(i.e. quantity limits) and consider scarcity message type(general scarcity message vs. special scarcity message), scarcity depth(high vs. low). The purpose of this study is to examine the effect of the scarcity message on the consumer's purchase intension. Specifically, we investigate the effect of general versus special scarcity messages on the consumer's purchase intention using the level of the scarcity depth as moderators. In other words, we postulates that the scarcity message type and scarcity depth play an essential moderating role in the relationship between the inferred motives and purchase intention. In other worlds, different from the past studies, we examine the interplay between the perceived motives and scarcity type, and between the perceived motives and scarcity depth. Both of these constructs have been examined in isolation, but a key question is whether they interact to produce an effect in reaction to the scarcity message type or scarcity depth increase. The perceived motive Inference behind the scarcity message will have important impact on consumers' reactions to the degree of scarcity depth increase. In relation ti this general question, we investigate the following specific issues. First, does consumers' inferred motives weaken the positive relationship between the scarcity depth decrease and the consumers' purchase intention, and if so, how much does it attenuate this relationship? Second, we examine the interplay between the scarcity message type and the consumers' purchase intention in the context of the scarcity depth decrease. Third, we study whether scarcity message type and scarcity depth directly affect the consumers' purchase intention. For the answer of these questions, this research is composed of 2(intention inference: existence vs. nonexistence)${\times}2$(scarcity type: special vs. general)${\times}2$(scarcity depth: high vs. low) between subject designs. The results are summarized as follows. First, intention inference(inferred motive) is not significant on scarcity effect in case of special scarcity message. However, nonexistence of intention inference is more effective than existence of intention inference on purchase intention in case of general scarcity. Second, intention inference(inferred motive) is not significant on scarcity effect in case of low scarcity. However, nonexistence of intention inference is more effective than existence of intention inference on purchase intention in case of high scarcity. The results of this study will help managers to understand the relative importance among the type of the scarcity message and to make decisions in using their scarcity message. Finally, this article have several contribution. First, we have shown that restrictions server to activates a mental resource that is used to render a judgment regarding a promoted product. In the absence of other information, this resource appears to read to an inference of value. In the presence of other value related cue, however, either database(i.e., scarcity depth: high vs. low) or conceptual base(i.e.,, scarcity type special vs. general), the resource is used in conjunction with the other cues as a basis for judgment, leading to different effects across levels of these other value-related cues. Second, our results suggest that a restriction can affect consumer behavior through four possible routes: 1) the affective route, through making consumers feel irritated, 2) the cognitive making route, through making consumers infer motivation or attribution about promoted scarcity message, and 3) the economic route, through making the consumer lose an opportunity to stockpile at a low scarcity depth, or forcing him her to making additional purchases, lastly 4) informative route, through changing what consumer believe about the transaction. Third, as a note already, this results suggest that we should consider consumers' inferences of motives or attributions for the scarcity dept level and cognitive resources available in order to have a complete understanding the effects of quantity restriction message.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Archives of design research
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• v.20 no.3 s.71
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• pp.29-38
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• 2007

The competition to capture a larger slice of the market in Mobile Communication business is increasing among companies. In order to achieve and maintain a competitive advantage in the Asian market, it is critical to continue to develop new technology. Understanding the underlying distinctive characteristics and needs of each market and the cultural backgrounds that drive those needs is a necessary focus. Companies with marketing strategies based on a correct understanding of market needs will capture dominant positions in the market. The purpose of this study is to identify those differences in user behavior and cultural tendencies among different people in different countries in the mobile telecommunication market. This research is based on an on-line survey in three countries (Korea, China, and Japan). Below are the contents of the survey on the mobile phone based on: 1) User behavior 2) Design preference 3) Purchasing behavior 4) User awareness on manufacturer brand. Through the analysis of this questionnaire it is possible to identify the differences and similarities among countries dearly. 1) Cultural trends and perceptions related to mobile phone usage were largely caused by differences in the state of technology, policies and business strategies of mobile sonics carriers and manufacturers, and national tendencies, of each country. 2) Korean and Japanese users produced similar responses to the questions related to advanced technology, whereas Korean and Chinese users responded similarly to national tendency-related questions. 3) To the questions related to business strategies of mobile service carriers and manufacturers, users in all three countries displayed markedly different responses. Once again, accurate analysis of the differences and similarities related to mobile phone usage in each country will help the companies in this industry to gain a competitive edge in the market. This study should not stop at simple comparison but be a framework for giving companies a dear future direction for technological development.

• Science of Emotion and Sensibility
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• v.19 no.4
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• pp.21-32
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• 2016

Studies have observed various phenomena regarding the effect of the interaction between type, price, and brand image of a product on consumers' purchase intent and product quality perception. Yet, few have studied the effect of the interaction between product type and manufacturing method on these factors. However, the advent of three-dimensional (3D) printers added a new manufacturing method, 3D printing, to the traditional methods of handicraft and automated machine-based production, and research is necessary since this new framework might affect consumers' purchase intent and product quality perception. Therefore, this study aimed to verify the effects of the interaction between product type and manufacturing method on purchase intent and product quality perception. To achieve this, in our experiment 1, we selected product types with different characteristics (drone vs. violin vs. cup), and measured whether consumers preferred different manufacturing methods for each product type. The results showed that consumers preferred the 3D printing method for technologically advanced products such as drones, the handmade method for violins, and the automated machine-based manufacturing method, which allows mass production, for cups. Experiment 2 attempted to verify the effects of the differences in manufacturing method preferences for each product type on consumers' purchase intent and product quality perception. Our findings are as follows: for drones, the purchase intent was highest when 3D printing was used; for violins, the purchase intent was highest when the violins were handmade; for cups, the purchase intent was highest when machine-based manufacturing was used. Moreover, whereas the product quality perception for drones did not differ across different manufacturing methods, consumers perceived that handmade violins had the highest quality and that cups manufactured with 3D printing had the lowest quality (the purchase intent for cups was also lowest when 3D printing was used). This study is anticipated to provide a wide range of implications in various areas, including consumer psychology, marketing, and advertising.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.4
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• pp.275-284
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• 2017

Rice quality should be considered as a primary consumer requirement. Regarding marketing, characteristics such as appearance, physicochemical properties, and palatability of brand rice are of high economic importance. Therefore, this study was conducted to select the optimal rice cultivars representing the commercial rice brands of Gyeongsangbuk-do province in Korea. Various rice grain quality components, grain appearance, several physicochemical properties of rice grain, and texture or palatability of cooked rice grains of ten cultivars (namely 'top quality rice') cultivated at three different locations, such as inland mountainous and southern plain areas of Gyeongsangbuk-do province in 2013~2014, were evaluated, and the obtained data was analyzed. 'Hiami' showed slightly higher protein contents and lower palatability of cooked rice than the other rice cultivars. Rice production and head rice yield produced at Gumi were the highest. The protein content of milled rice produced at Andong, an inland mountainous region, was approximately 0.3% point lower than that from other locations, whereas the amylose content of milled rice was approximately 1% point higher than those from the other plain regions, Daegu and Gumi. We evaluated the texture, Glossiness value determined using a Toyo teste meter and palatability of cooked rice of ten cultivars. The hardness of cooked rice produced in Andong was slightly lower than that produced in Daegu and Gumi, and additionally, the palatability of cooked rice produced in Andong was the best, followed by that producted in Gumi and Daegu. Considering rice yield and grain quality in the major rice cultivation areas of Gyeongsangbuk-do province, the rice cultivars that may be suitable for each region could be recommended mid-late maturation: 'Younghojinmi' and 'Mipum' in Daegu, 'Daebo', 'Samgwang', Chilbo' and 'Younghojinmi' in Gumi, 'Samgwang', 'Jinsumi' and 'Sukwang' in Andong. These results obtained in this study imply that the selected cultivars with high yield and quality could be recommended with high priority to rice farmers in the regions.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.59-69
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• 2012

As exhibition industry, which is a part of 17 new growth engines of the government, is related to other industries such as tourism, transportation and financial industries. So it has a significant ripple effect on other industries. Exhibition is a knowledge-intensive, eco-friendly and high value-added Industry. Over 13,000 exhibitions are held every year around the world which contributes to getting foreign currency. Exhibition industry is closely related with culture and tourism and could be utilized as local and national development strategies and improve national brand image as well. Many countries try various efforts to invigorate exhibition industry by arranging related laws and support system. In Korea, more than 200 exhibitions are being held every year, but only 2~3 exhibitions are hosted with over 400 exhibitors and except these exhibitions most exhibitions have few foreign exhibitors. The main reason of weakness of domestic trade show is that there are no agencies managing exhibitionrelated statistics and there is no specific and reliable evaluation. This might cause impossibility of providing buyer or seller with reliable data, poor growth of exhibitions in terms of quality and thus service quality of trade shows cannot be improved. Hosting a lot of visitors (Public/Buyer/Exhibitor) is very crucial to the development of domestic exhibition industry. In order to attract many visitors, service quality of exhibition and visitor's satisfaction should be enhanced. For this purpose, a variety of real-time customized services through digital media and the services for creating new customers and retaining existing customers should be provided. In addition, by providing visitors with personalized information services they could manage their time and space efficiently avoiding the complexity of exhibition space. Exhibition industry can have competitiveness and industrial foundation through building up exhibition-related statistics, creating new information and enhancing research ability. Therefore, this paper deals with customized service with visitor's smart-phone at the exhibition space and designing mobile framework which enables exhibition devices to interact with other devices. Mobile server framework is composed of three different systems; multi-server interaction, server, client, display device. By making knowledge pool of exhibition environment, the accumulated data for each visitor can be provided as personalized service. In addition, based on the reaction of visitors each of all information is utilized as customized information and so the cyclic chain structure is designed. Multiple interaction server is designed to have functions of event handling, interaction process between exhibition device and visitor's smart-phone and data management. Client is an application processed by visitor's smart-phone and could be driven on a variety of platforms. Client functions as interface representing customized service for individual visitors and event input and output for simultaneous participation. Exhibition device consists of display system to show visitors contents and information, interaction input-output system to receive event from visitors and input toward action and finally the control system to connect above two systems. The proposed mobile framework in this paper provides individual visitors with customized and active services using their information profile and advanced Knowledge. In addition, user participation service is suggested as well by using interaction connection system between server, client, and exhibition devices. Suggested mobile framework is a technology which could be applied to culture industry such as performance, show and exhibition. Thus, this builds up the foundation to improve visitor's participation in exhibition and bring about development of exhibition industry by raising visitor's interest.