• Journal of Digital Convergence
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• v.19 no.5
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• pp.105-115
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• 2021

Many services are provided through big data analysis in various fields such as individuals, private sectors, and governments. There is a growing interest in training data scientists to provide these services. Particularly, interest in big data-based marketing curriculum is high. This study analyzed the domestic and foreign university big data-based marketing-related curriculum to utilize vast and diverse types of information from a marketing perspective in the era of big data. As a result of the analysis of 3,523 subjects related to digital marketing, big data marketing, data analysis, and developers collected according to the analysis criteria, it was analyzed that the specialized curriculum for training data scientists required in the era of the fourth industrial revolution was not appropriate. It is expected that the proposed curriculum in this study will be useful for the development of digital marketing and big data-based marketing curriculum.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.55-63
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• 2016

SOA(service oriented architecture) based ESB(enterprise service bus) model is widely adopted in many companies for the safe processing of enormous data and the integration of business system. The existing web service technologies for the construction of SOA, however, show unsatisfactory in practical applications though the standardization of web service security technologies is in progress due to their limitations in safe exchange of data. Internal end users using a large business system based on such environment are composed of the variety of organizations and roles. Companies might receive more serious damage from insider threat than that from external one when internal end users get unauthorized information beyond the limits of their authority for private profit and bad purposes. In this paper, we propose a security architecture capable of identifying and coping with the security threats of web service technologies arouse from internal end users.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.4
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• pp.173-194
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• 2011

This paper analyzes quantitative economic effect of accuracy improvement in location based services. This analysis is motivated from the situation that Korea Communications Commission is preparing the notification for 'location accuracy standard.' The analysis includes three level of impacts. Firm level analyzes the impact on revenue of firms. Social level additionally includes consumers' surplus in LBS industry. Lastly, economywide level includes ripple effects to another industries, which uses input-output analysis. The result of analysis shows that the economic value reaches to considerable amount and cost-benefit ratio is considerably high. The consumers' surplus is much larger than revenue increase. This result supports the intuition that many of location based services are for public interest and that the services have much externalities among firms and consumers. This means that the role of government is very important in the execution of accuracy improvement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.157-165
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• 2015

With the ever-improving performance of smartphone cameras and the universal dissemination of cloud services, users can now record and store the events in their daily lives more easily and conveniently. The advent of lifelogging technology has been changing the uses as well as the paradigm of internet services, and emphasizing the importance of services being personalization. As the amount of lifelog data becomes vast, it requires an efficient way to manage and store such vast information. In this paper, we propose an low power lifelog management scheme based on user movement behaviors in wireless networks. In order to reduce the power consumption of a smartphone, in our proposal, frequency of data collection and transfer can be dynamically adjusted based on a user's movement pattern. The analytical results show that our approach achieves better performance than that of the existing lifelog management scheme.

• 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 the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1283-1292
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• 2012

As delivery services market has grown the damage cases are also continuously increased. When using delivery services, Customers would not be compensated in any way. Perhaps worse, losing a cargo would create a great deal of trouble. Because the lack of evidence, they takes a lot of time to clarify who is responsible. To prevent these things, we must create, collect, maintain and confirm. In this paper, we introduce new delivery system with a trusted third party for non-repudiation services. Moreover, in damage case, we show that the proposed system is efficient and provide non-repudiation. Using sending and receiving codes, the proposed system identifies a responsible subject with quickness and clearness.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.283-293
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• 2012

A new type of malware that extracts personal and account data over an extended period of time and that apparently is resistant to detection by vaccines has been identified. Generally, a malware is installed on a computer through network-to-network connections by utilizing Web vulnerabilities that contain injection, XSS, broken authentication and session management, or insecure direct-object references, among others. After the malware executes registration of an arbitrary service and an arbitrary process on a computer, it then periodically communicates the collected confidential information to a hacker. This paper is a systematic approach to analyzing a new type of malware called "winweng," a kind of worm that frequently made appearances during the first half of 2011. The research describes how the malware came to be in circulation, how it infects computers, how its operations expose its existence and suggests improvements in responses and countermeasures. Keywords: Malware, Worm, Winweng, SNORT.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.157-175
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• 2013

Since Korean government announced 'Smartwork promotion strategy' in 2010, Korean firms and government organizations have started to adopt smartwork. However, the smartwork has been implemented only in a few of large enterprises and government organizations rather than SMEs (small and medium enterprises). In USA, both Yahoo! and Best Buy have stopped their flexible work because of its reported low productivity and job loafing problems. In addition, according to the literature on smartwork, we could draw obstacles of smartwork adoption and categorize them into the three types: institutional, organizational, and technological. The first category of smartwork adoption obstacles, institutional, include the difficulties of smartwork performance evaluation metrics, the lack of readiness of organizational processes, limitation of smartwork types and models, lack of employee participation in smartwork adoption procedure, high cost of building smartwork system, and insufficiency of government support. The second category, organizational, includes limitation of the organization hierarchy, wrong perception of employees and employers, a difficulty in close collaboration, low productivity with remote coworkers, insufficient understanding on remote working, and lack of training about smartwork. The third category, technological, obstacles include security concern of mobile work, lack of specialized solution, and lack of adoption and operation know-how. To overcome the current problems of smartwork in reality and the reported obstacles in literature, we suggest a novel smartwork service model based on NFC(Near Field Communication). This paper suggests NFC-based Smartwork Service Model composed of NFC-based Smartworker networking service and NFC-based Smartwork space management service. NFC-based smartworker networking service is comprised of NFC-based communication/SNS service and NFC-based recruiting/job seeking service. NFC-based communication/SNS Service Model supplements the key shortcomings that existing smartwork service model has. By connecting to existing legacy system of a company through NFC tags and systems, the low productivity and the difficulty of collaboration and attendance management can be overcome since managers can get work processing information, work time information and work space information of employees and employees can do real-time communication with coworkers and get location information of coworkers. Shortly, this service model has features such as affordable system cost, provision of location-based information, and possibility of knowledge accumulation. NFC-based recruiting/job-seeking service provides new value by linking NFC tag service and sharing economy sites. This service model has features such as easiness of service attachment and removal, efficient space-based work provision, easy search of location-based recruiting/job-seeking information, and system flexibility. This service model combines advantages of sharing economy sites with the advantages of NFC. By cooperation with sharing economy sites, the model can provide recruiters with human resource who finds not only long-term works but also short-term works. Additionally, SMEs (Small Medium-sized Enterprises) can easily find job seeker by attaching NFC tags to any spaces at which human resource with qualification may be located. In short, this service model helps efficient human resource distribution by providing location of job hunters and job applicants. NFC-based smartwork space management service can promote smartwork by linking NFC tags attached to the work space and existing smartwork system. This service has features such as low cost, provision of indoor and outdoor location information, and customized service. In particular, this model can help small company adopt smartwork system because it is light-weight system and cost-effective compared to existing smartwork system. This paper proposes the scenarios of the service models, the roles and incentives of the participants, and the comparative analysis. The superiority of NFC-based smartwork service model is shown by comparing and analyzing the new service models and the existing service models. The service model can expand scope of enterprises and organizations that adopt smartwork and expand the scope of employees that take advantages of smartwork.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.24-35
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• 2011

This paper demonstrates a methodology of integrated operation and management system for intermodal connectivity center (ICC), which is planning to be build up as a large scale public transit facilities for green growth strategy by the national government. The ICC needs to be capable of providing the integrated location based information for the public transit users in terms of collaborating a variety of transit modes and complex facility in a large scale center. Recently, the upcoming information and communication technologies enable to come up with real time information provision on nomadic and portable devices, i.e. smart phones and/or tablet PCs, as what the users actually need to get on demand. In order to provide the public transit users in ICC with the integrated information on their smart phones for example, the integrated operation and management system plays a key role to collect the data utilizing the wireless communication with real time location tracking and to manage them to be effective and operational sources for applicable personalized services. Thus, this paper defines a type of services, subsystems, and relevant technologies for the system integration so called a "Smart Garatagi Service" and shows a filed test demonstration case in the existing airport terminal, Gimpo Domestic.