• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.95-117
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• 2022

With the emergence of various media types due to the development of Internet technology, advertisers have difficulty choosing media suitable for corporate advertising strategies. There are challenging to effectively reflect consumer contextual information when advertising media is selected based on traditional marketing strategies. Thus, a recommender system is needed to analyze consumers' past data and provide advertisers with personalized media based on the information consumers needs. Since the traditional recommender system provides recommendation services based on quantitative preference information, there is difficult to reflect various contextual information. This study proposes a methodology that uses deep learning to recommend personalized media to advertisers using consumer contextual information such as consumers' media viewing time, residence area, age, and gender. This study builds a recommender system using media & consumer research data provided by the Korea Broadcasting Advertising Promotion Corporation. Additionally, we evaluate the recommendation performance compared with several benchmark models. As a result of the experiment, we confirmed that the recommendation model reflecting the consumer's contextual information showed higher accuracy than the benchmark model. We expect to contribute to helping advertisers make effective decisions when selecting customized media based on various contextual information of consumers.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.195-211
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• 2010

An exhibition is defined as market events for specific duration to present exhibitors' main product range to either business or private visitors, and it also plays a key role as effective marketing channels. Especially, as the effect of the opinions of the visitors after the exhibition impacts directly on sales or the image of companies, exhibition organizers must consider various needs of visitors. To meet needs of visitors, ubiquitous technologies have been applied in some exhibitions. However, despite of the development of the ubiquitous technologies, their services cannot always reflect visitors' preferences as they only generate information when visitors request. As a result, they have reached their limit to meet needs of visitors, which consequently might lead them to loss of marketing opportunity. Recommendation systems can be the right type to overcome these limitations. They can recommend the booths to coincide with visitors' preferences, so that they help visitors who are in difficulty for choices in exhibition environment. One of the most successful and widely used technologies for building recommender systems is called Collaborative Filtering. Traditional recommender systems, however, only use neighbors' evaluations or behaviors for a personalized prediction. Therefore, they can not reflect visitors' dynamic preference, and also lack of accuracy in exhibition environment. Although there is much useful information to infer visitors' preference in ubiquitous environment (e.g., visitors' current location, booth visit path, and so on), they use only limited information for recommendation. In this study, we propose a booth recommendation methodology using Sequential Association Rule which considers the sequence of visiting. Recent studies of Sequential Association Rule use the constraints to improve the performance. However, since traditional Sequential Association Rule considers the whole rules to recommendation, they have a scalability problem when they are adapted to a large exhibition scale. To solve this problem, our methodology composes the confidence database before recommendation process. To compose the confidence database, we first search preceding rules which have the frequency above threshold. Next, we compute the confidences of each preceding rules to each booth which is not contained in preceding rules. Therefore, the confidence database has two kinds of information which are preceding rules and their confidence to each booth. In recommendation process, we just generate preceding rules of the target visitors based on the records of the visits, and recommend booths according to the confidence database. Throughout these steps, we expect reduction of time spent on recommendation process. To evaluate proposed methodology, we use real booth visit records which are collected by RFID technology in IT exhibition. Booth visit records also contain the visit sequence of each visitor. We compare the performance of proposed methodology with traditional Collaborative Filtering system. As a result, our proposed methodology generally shows higher performance than traditional Collaborative Filtering. We can also see some features of it in experimental results. First, it shows the highest performance at one booth recommendation. It detects preceding rules with some portions of visitors. Therefore, if there is a visitor who moved with very a different pattern compared to the whole visitors, it cannot give a correct recommendation for him/her even though we increase the number of recommendation. Trained by the whole visitors, it cannot correctly give recommendation to visitors who have a unique path. Second, the performance of general recommendation systems increase as time expands. However, our methodology shows higher performance with limited information like one or two time periods. Therefore, not only can it recommend even if there is not much information of the target visitors' booth visit records, but also it uses only small amount of information in recommendation process. We expect that it can give real?time recommendations in exhibition environment. Overall, our methodology shows higher performance ability than traditional Collaborative Filtering systems, we expect it could be applied in booth recommendation system to satisfy visitors in exhibition environment.

• Journal of Distribution Science
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• v.8 no.3
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• pp.49-56
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• 2010

At the initial stage of Internet advertising, banner advertising came into fashion. As the Internet developed into a central part of daily lives and the competition in the on-line advertising market was getting fierce, there was not enough space for banner advertising, which rushed to portal sites only. All these factors was responsible for an upsurge in advertising prices. Consequently, the high-cost and low-efficiency problems with banner advertising were raised, which led to an emergence of keyword advertising as a new type of Internet advertising to replace its predecessor. In the beginning of 2000s, when Internet advertising came to be activated, display advertisement including banner advertising dominated the Net. However, display advertising showed signs of gradual decline, and registered minus growth in the year 2009, whereas keyword advertising showed rapid growth and started to outdo display advertising as of the year 2005. Keyword advertising refers to the advertising technique that exposes relevant advertisements on the top of research sites when one searches for a keyword. Instead of exposing advertisements to unspecified individuals like banner advertising, keyword advertising, or targeted advertising technique, shows advertisements only when customers search for a desired keyword so that only highly prospective customers are given a chance to see them. In this context, it is also referred to as search advertising. It is regarded as more aggressive advertising with a high hit rate than previous advertising in that, instead of the seller discovering customers and running an advertisement for them like TV, radios or banner advertising, it exposes advertisements to visiting customers. Keyword advertising makes it possible for a company to seek publicity on line simply by making use of a single word and to achieve a maximum of efficiency at a minimum cost. The strong point of keyword advertising is that customers are allowed to directly contact the products in question through its more efficient advertising when compared to the advertisements of mass media such as TV and radio, etc. The weak point of keyword advertising is that a company should have its advertisement registered on each and every portal site and finds it hard to exercise substantial supervision over its advertisement, there being a possibility of its advertising expenses exceeding its profits. Keyword advertising severs as the most appropriate methods of advertising for the sales and publicity of small and medium enterprises which are in need of a maximum of advertising effect at a low advertising cost. At present, keyword advertising is divided into CPC advertising and CPM advertising. The former is known as the most efficient technique, which is also referred to as advertising based on the meter rate system; A company is supposed to pay for the number of clicks on a searched keyword which users have searched. This is representatively adopted by Overture, Google's Adwords, Naver's Clickchoice, and Daum's Clicks, etc. CPM advertising is dependent upon the flat rate payment system, making a company pay for its advertisement on the basis of the number of exposure, not on the basis of the number of clicks. This method fixes a price for advertisement on the basis of 1,000-time exposure, and is mainly adopted by Naver's Timechoice, Daum's Speciallink, and Nate's Speedup, etc, At present, the CPC method is most frequently adopted. The weak point of the CPC method is that advertising cost can rise through constant clicks from the same IP. If a company makes good use of strategies for maximizing the strong points of keyword advertising and complementing its weak points, it is highly likely to turn its visitors into prospective customers. Accordingly, an advertiser should make an analysis of customers' behavior and approach them in a variety of ways, trying hard to find out what they want. With this in mind, her or she has to put multiple keywords into use when running for ads. When he or she first runs an ad, he or she should first give priority to which keyword to select. The advertiser should consider how many individuals using a search engine will click the keyword in question and how much money he or she has to pay for the advertisement. As the popular keywords that the users of search engines are frequently using are expensive in terms of a unit cost per click, the advertisers without much money for advertising at the initial phrase should pay attention to detailed keywords suitable to their budget. Detailed keywords are also referred to as peripheral keywords or extension keywords, which can be called a combination of major keywords. Most keywords are in the form of texts. The biggest strong point of text-based advertising is that it looks like search results, causing little antipathy to it. But it fails to attract much attention because of the fact that most keyword advertising is in the form of texts. Image-embedded advertising is easy to notice due to images, but it is exposed on the lower part of a web page and regarded as an advertisement, which leads to a low click through rate. However, its strong point is that its prices are lower than those of text-based advertising. If a company owns a logo or a product that is easy enough for people to recognize, the company is well advised to make good use of image-embedded advertising so as to attract Internet users' attention. Advertisers should make an analysis of their logos and examine customers' responses based on the events of sites in question and the composition of products as a vehicle for monitoring their behavior in detail. Besides, keyword advertising allows them to analyze the advertising effects of exposed keywords through the analysis of logos. The logo analysis refers to a close analysis of the current situation of a site by making an analysis of information about visitors on the basis of the analysis of the number of visitors and page view, and that of cookie values. It is in the log files generated through each Web server that a user's IP, used pages, the time when he or she uses it, and cookie values are stored. The log files contain a huge amount of data. As it is almost impossible to make a direct analysis of these log files, one is supposed to make an analysis of them by using solutions for a log analysis. The generic information that can be extracted from tools for each logo analysis includes the number of viewing the total pages, the number of average page view per day, the number of basic page view, the number of page view per visit, the total number of hits, the number of average hits per day, the number of hits per visit, the number of visits, the number of average visits per day, the net number of visitors, average visitors per day, one-time visitors, visitors who have come more than twice, and average using hours, etc. These sites are deemed to be useful for utilizing data for the analysis of the situation and current status of rival companies as well as benchmarking. As keyword advertising exposes advertisements exclusively on search-result pages, competition among advertisers attempting to preoccupy popular keywords is very fierce. Some portal sites keep on giving priority to the existing advertisers, whereas others provide chances to purchase keywords in question to all the advertisers after the advertising contract is over. If an advertiser tries to rely on keywords sensitive to seasons and timeliness in case of sites providing priority to the established advertisers, he or she may as well make a purchase of a vacant place for advertising lest he or she should miss appropriate timing for advertising. However, Naver doesn't provide priority to the existing advertisers as far as all the keyword advertisements are concerned. In this case, one can preoccupy keywords if he or she enters into a contract after confirming the contract period for advertising. This study is designed to take a look at marketing for keyword advertising and to present effective strategies for keyword advertising marketing. At present, the Korean CPC advertising market is virtually monopolized by Overture. Its strong points are that Overture is based on the CPC charging model and that advertisements are registered on the top of the most representative portal sites in Korea. These advantages serve as the most appropriate medium for small and medium enterprises to use. However, the CPC method of Overture has its weak points, too. That is, the CPC method is not the only perfect advertising model among the search advertisements in the on-line market. So it is absolutely necessary that small and medium enterprises including independent shopping malls should complement the weaknesses of the CPC method and make good use of strategies for maximizing its strengths so as to increase their sales and to create a point of contact with customers.

• Journal of the Korean Society for Marine Environment & Energy
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• v.16 no.1
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• pp.17-24
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• 2013

In order to have market competitiveness in local and global areas, Domestic Marine Leisure Industry business, which is a latecomer in the Marine Leisure industry, should retain a strong market adaptability by reducing time and cost that are required for work of planning, designing, and preparation for product development. To meet above requirements, it is essential that integrated system control extensive marine leisure industry. After ensuring integrated information by figuring out the systematic link between related-industries, the core of this research is to secure information classifications that are not just in the flow of simple serial order, but in that of integration and object-oriented information classifications. For this end, we examine other similar cases in industries using real information system applied to industrial production and Product Lifecycle Management (PLM), Product Data Management (PDM), Digital Manufacturing (DM) and applying the same methodology to review practical application in order to construct the information system, and Work Breakdown Structure (WBS), compared with the case studies. Through this basic task for the marine leisure industry classification system configuration (Work Breakdown Structure, WBS) and utilizing information of driving real companies of marine leisure industry, a unique area of MLWBS (Marine Leisure Work Breakdown Structure, MLWBS) is configured. This Marine Leisure Work Breakdown Structure can be used in various areas of applications like products, design information, engineering, production, purchasing, sales, marketing, AS, utilizing various forms of customer support.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.151-160
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• 2015

As a lexical meaning, casino is defined as "a certified gambling house, equipped with recreational facilities such as dance and music, etc., where people play roulette or cards." Casinos started from 17th to 18th century for European nobility and their social meetings and established a casino industry framework in the United States in the 1930s. The success of the casino business leads to the increase of sales; it became very helpful for the local and national government revenues and also for the related incidental tasks. Casino operations include a variety of fields, such as general customer management, dealer game management, security, account management, currency exchange, re-exchange management, marketing management, comp management and placement management, etc. These operations should be organically connected to each other by information systems such as a groupware, ERP and Customer Relationship Management (CRM), etc. In addition, in order to effectively manage comprehensive entertainment service, including accommodation and tourism, it is necessary to develop an information system which supports casino business and collateral entertainment service, collects the data generated throughout the business and provides information about the situations of management. Thus, this study will propose a casino information system designed and implemented, considering these details.

• Archives of design research
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• v.17 no.2
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• pp.279-288
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• 2004

Corporate design activities have expanded from being exclusive and passive responsibilities to active participation in planning, marketing, technology and corporate brand image differentiation for successful business. Thus the communications between designers and other functions come to include critical decision making, information sharing, and objective reasoning. Given that design activities now have to involve various functions in product development, the styling-related design process, which is still developed by designer's intuition and experience, poses as an obstacle not just between various functions involved, but even within the design function. To overcome this obstacle and to lead more effective design decision process, a means for product form development assessment and management is necessary. This research proposes a foundation for managing and assessing product form based on the hypothesis and demonstration of discovering a system of formative factor and order a product form expresses that can be shared as an objective and logical system. As a result of this demonstration, the form as a unique visual expression and the factors related to the form and its co-relationship are examined. The factors are called formative parameters and the system is named as the product form alignment method. Based on the logic derived from the system, the process for developing an image that aligns with the predefined goal is explained. The method defines a balance between a designer's intuitive creativity and the extracted logic, which can act as a basis for designers to share design language among themselves and for communication between design and other functions. Based on this system, designers are able to align design work with the set goal, and focus and limit the range of form development, which is anticipated to result in lead-time reduction and minimizing unnecessary obstacles and mistakes.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.153-177
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• 2001

Nowadays, product recommendation is one of the important issues regarding both CRM and Internet shopping mall. Generally, a recommendation system tracks past actions of a group of users to make a recommendation to individual members of the group. The computer-mediated marketing and commerce have grown rapidly and thereby automatic recommendation methodologies have got great attentions. But the researches and commercial tools for product recommendation so far, still have many aspects that merit further considerations. To supplement those aspects, we devise a recommendation methodology by which we can get further recommendation effectiveness when applied to Internet shopping mall. The suggested methodology is based on web log information, product taxonomy, association rule mining, and decision tree learning. To implement this we also design and intelligent Internet shopping mall support system based on agent technology and develop it as a prototype system. We applied this methodology and the prototype system to a leading Korean Internet shopping mall and provide some experimental results. Through the experiment, we found that the suggested methodology can perform recommendation tasks both effectively and efficiently in real world problems. Its systematic validity issues are also discussed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.373-383
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• 2015

Spatial information has been widely used for efficient land use and management, disaster management, environment management, infrastructure management, corporate marketing, and cultural assets management, and the need for spatial information is expected to be increased. For this reason, central government, local government and public institutions must establish a National Spatial Information System (Fifteen systems related to spatial information managed by National Spatial Data Infrastructure Policy office, NSIS) framework that guarantees high accuracy and quality. The NSIS will provide convenience usage of spatial information in the field of decision-making or civil support. However the current National Spatial Information System is mainly established with separate processes, which causes data redundancy, deterioration of information, passive opening, and sharing of the spatial data. This study suggests 4 standards, which has been derived by applying value-chain model to NSIS data flow, and they are ‘Production and Establishment’, ‘Integration and Sharing’, ‘Application and Fusion’ and ‘Release and Opening’. Based on these standards, the 15 NSIS were analyzed to draw out implications and reforming directions were suggested. By following these suggestions we expect more recent, consist, accurate, and connected National Spatial Information Service which will be more open to public and then satisfy the demands.

• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.51-71
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• 2017

This study conducted a survey to measure recognition distance between the materials which are located separately in a children's library targeting 200 elementary school lower grade students, higher grade students, and school parents(adults). And compared recognition distance between the elements of materials of individual visitor group with multidimensional scaling and K-mean group analysis. Multidimensional Scaling (MDS) is a technique for projecting the cognitive state in space by evaluating the similarity or attribute of the analysis target. Even though it is mainly used for market diagnosis in marketing, It can also be applied to present an ideal physical layout plan by analyzing the distance. As a result of analysis, the main discoveries are as follows. First, elementary school students cognize child, baby and computer materials should be adjacent as a same group. But recognition of adults(school parents) is reflected by differing from elementary school students vastly. They cognize that computer materials should be formed as a special group separated from child and baby's materials. Second, elementary school higher graders and adults(school parents) groups also want to separate their main reading materials from baby's book, therefore They both want to secure silent reading space separating from baby. Third, as a result to confirming how this recognition distance system of materials is reflected in a real children's library through three children's libraries in Y-gu, Incheon, there is no library with structure according perfectly with a recognition system of a particular class, but a recognition system of adults and elementary school students is partially reflected because baby, child and computer materials, and baby and child materials are commonly separated and placed. It is difficult to insist that a recognition system of a visitor group, especially a recognition system of children is absolute consideration conditions in material placement of a children's library. However, understanding cognition of the user groups can be an important evidentiary factors to offer differentiated service space according to visitors and effective placement of the elements of library resources.

• Journal of Global Scholars of Marketing Science
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• v.20 no.3
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• pp.249-261
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• 2010

As consumers' concern for the environment has continued to increase, many firms have actively engaged in environmental marketing to achieve their objectives. However, consumers' high concerns about the environment are not always reflected in their purchasing behavior. This indicates the need for an in-depth understanding of the development of green consumption within the individual's belief system. In consideration of psychological approaches, a large body of research has examined the factors underlying ecologically conscious "green" consumer behavior and the interrelationships of these factors. However, most previous studies have concentrated on Western countries. Using a sample of Korean consumers, this study attempts to understand the basis of Korean green consumerism and find universal values that are cross-culturally important in guiding consumers' environmental attitudes and behaviors. To this end, this study relates Schwartz's 10 universal values (Schwartz 1992) to environmental behaviors in a hierarchical model of value-attitude-behavior. With reference to the value-attitude-behavior framework, the conceptual model developed for the study explains what motivations can be manifested in Korean consumers' environmental attitudes, and subsequently how the attitudes affect their green choices. Using the pattern of relationships among values that can be related to environmentalism, the first hypothesis holds that there would be particular relationships between motivational value types and environmental attitudes. Hypothesis 2 assumes that environmental attitudes predict environmental behaviors. On the basis of the claim that favorable attitudes toward the environment may be expressed in many different behaviors, the assumption is that consumers' favorable attitudes toward the environment would be linked to a variety of environmental behaviors because people with high environmental attitudes can be more interested in and knowledgeable about environmental actions. Consistent with H2, H3 hypothesizes that there would be a positive relationship between different types of environmental behavior. A total of 564 university students participated in the study. The sample included 308 men, 254 women, and two participants who did not indicate their gender. The average age of the participants was 22.5 years, with a range of 19 to 39. Regarding majors, special efforts were made to draw the participants from different departments of the university. Data were collected by a survey administered via self-completion questionnaires., which assessed the participants' value priorities, environmental attitudes, and behaviors. Path analysis conducted to test the proposed model found the overall fit to be ${\chi}^2$=72.01 (p=0.00), GFI=0.983, CFI=0.982, NFI=0.970, RMR=0.070, and REMSEA=0.050. Thus, most of the fit measures indicated a good fit of the model with the data, and a hierarchical relationship from values to environmental attitudes to environmental non-purchasing behavior to environmental purchasing behavior was confirmed. An assessment of all the predicted paths by path coefficients led to several major hypothesized effects being confirmed. Out of the ten value types, universalism and power were significantly but conversely related to environmental attitudes. In line with the other studies, these findings confirm that environmental attitudes are an important factor in leading to a variety of green behaviors. Finally, significant relationships were found between environmental purchasing and non-purchasing behaviors. The path analysis supported the idea that universalism values provide a motivation for Korean consumers' greenness and indirectly promote environmental acts through favorable attitudes toward the environment. Participants with high environmental attitudes were found to actively engage in diverse forms of green consumer behavior. This research provides an opportunity to examine cross-cultural differences with respect to values leading to environmentalism, and, further, to verify previous findings. The study also examined the attitude-behavior relationship with respect to three distinct types of environmental behaviors. The different strengths of paths between green attitudes and behaviors suggest that researchers should consider the specificity of behavior explained as an effort to improve the low attitude-behavior correlation. Finally, the findings here illustrate that with increased environmental concerns among people, they come to include more such behaviors in their green portfolios.