• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1767-1777
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• 2010

In digital TV broadcasting, such as terrestrial, cable, satellite, and IPTV, the head-end of digital TV broadcasting has a more complicated transmission structure than that of analog TV broadcasting. Furthermore, digital TV broadcasting has a feature that supports multiplex models, such as Multiple Program Transport Stream (MPTS). Therefore, the purpose of our work was to design and examine a more efficient new system of emergency alert message transmission to support the digital TV broadcasting environments. Digital TV broadcasting is the IP generation or RF transmission of 8-VSB, QAM, and QPSK modulated through a multiplexer or re-multiplexer multiplexed stream as a MPEG-2 Transport Stream after content encoding. The new system proposed in this paper transmits an emergency alert message without scrambling after replacing the PID and payload of the -packet with the message prototype in the TS stream from the multiplexer. If we need to transmit an emergency alert message under digital TV broadcasting services, then the receiver first checks the PID of each packet in the TS stream for the emergency alert message. Next, if a packet is determined to be an emergency alert message, then the set-top box displays the message on the TV screen using its function of On Screen Display, or the PC based software displays the message on the monitor screen using its function of overlay with user interface if the packet is found to be an emergency alert message. We have designed an emergency alert message protocol and a system model. By experiments and analysis of the system, we concluded that the system achieved efficiency and the ability to send and receive emergency alert messages using the system under different digital TV broadcasting service environments.

• The KIPS Transactions:PartC
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• v.15C no.6
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• pp.557-566
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• 2008

NGN(Next Generation Network) is a communication network which can make use of broadband and QoS-enabled transport technologies. One of the main service issues over NGN is a multimedia service, such as IPTV, using a multicast method. And overlay multicast technology is one of the promising solutions instead of traditional multicast technology which has a few problems, and supports flexibility and scalability for multicast services. Also, the main controversial topic in NGN and overlay multicast is QoS. In the present paper, we designed an agent in each receiver's network, and a manager which is in a source network and which manages the whole multicast network. Both of them are communicating with each other and applying resource policies to their multicast network. This mechanism enables overlay multicast to support QoS, focusing on RACF(Resource and Admission Control Functions) in NGN QoS architecture.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.518-527
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• 2014

This study is to estimate the learning curve based on the consequences of reduced voice of customer from each telecommunication service products. We used Exponential Decay Model, which is the most popular among the learning curve models. We attempted to add how VOC changes in accordance with seasonal factors, human resource input, application of software, and the investment. The results of the empirical analysis of each service product as follows: First, as learning curve, customer complaints decreased. Second, human resource input, Network fault make increase or decrease customer complaints(VOC). Third, even though increasing the customer's quality of experience, VOC would not decrease due to service paradox.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.61-75
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• 2011

A Geographic Information System(GIS) is a system that captures, stores, analyzes, manages and presents data with reference to geographic location data. In the later 1990s and earlier 2000s it was limitedly used in government sectors such as public utility management, urban planning, landscape architecture, and environmental contamination control. However, a growing number of open-source packages running on a range of operating systems enabled many private enterprises to explore the concept of viewing GIS-based sales and customer data over their own computer monitors. K telecommunication company has dominated the Korean telecommunication market by providing diverse services, such as high-speed internet, PSTN(Public Switched Telephone Network), VOLP (Voice Over Internet Protocol), and IPTV(Internet Protocol Television). Even though the telecommunication market in Korea is huge, the competition between major services providers is growing more fierce than ever before. Service providers struggled to acquire as many new customers as possible, attempted to cross sell more products to their regular customers, and made more efforts on retaining the best customers by offering unprecedented benefits. Most service providers including K telecommunication company tried to adopt the concept of customer relationship management(CRM), and analyze customer's demographic and transactional data statistically in order to understand their customer's behavior. However, managing customer information has still remained at the basic level, and the quality and the quantity of customer data were not enough not only to understand the customers but also to design a strategy for marketing and sales. For example, the currently used 3,074 legal regional divisions, which are originally defined by the government, were too broad to calculate sub-regional customer's service subscription and cancellation ratio. Additional external data such as house size, house price, and household demographics are also needed to measure sales potential. Furthermore, making tables and reports were time consuming and they were insufficient to make a clear judgment about the market situation. In 2009, this company needed a dramatic shift in the way marketing and sales activities, and finally developed a dedicated GIS_based market analysis and sales management system. This system made huge improvement in the efficiency with which the company was able to manage and organize all customer and sales related information, and access to those information easily and visually. After the GIS information system was developed, and applied to marketing and sales activities at the corporate level, the company was reported to increase sales and market share substantially. This was due to the fact that by analyzing past market and sales initiatives, creating sales potential, and targeting key markets, the system could make suggestions and enable the company to focus its resources on the demographics most likely to respond to the promotion. This paper reviews subjective and unclear marketing and sales activities that K telecommunication company operated, and introduces the whole process of developing the GIS information system. The process consists of the following 5 modules : (1) Customer profile cleansing and standardization, (2) Internal/External DB enrichment, (3) Segmentation of 3,074 legal regions into 46,590 sub_regions called blocks, (4) GIS data mart design, and (5) GIS system construction. The objective of this case study is to emphasize the need of GIS system and how it works in the private enterprises by reviewing the development process of the K company's market analysis and sales management system. We hope that this paper suggest valuable guideline to companies that consider introducing or constructing a GIS information system.

• Journal of Legislation Research
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• no.41
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• pp.401-434
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• 2011

The discussion on the adoption of the horizontal regulatory framework is underway to overcome the problems regarding the vertical regulatory framework resulting from a convergence of broadcasting and telecommunications services. Recently, however, the horizontal regulatory framework shows its limitation to regulate the ecosystem established mainly by Google and Apple. The existing horizontal regulatory framework does not fully reflect the characteristics of the two-sided market and the change in the competition structure in the broadcasting and telecommunications sector. What is important to note is that if the existing horizontal regulatory framework is simply applied to the ecosystem, a regulatory imbalance can be caused among ecosystems. The existing horizontal regulatory framework, which is subject to a value chain structure, categorizes business entities into either contents layer or transmission layer and applies the same regulation to all business entities in the same category. However, in the ecosystem, a keystone-player can be categorized into different layers depending on its strategy. Therefore, if the existing horizontal regulatory framework is applied as it is, the regulatory imbalance between keystone-players located in less regulated areas and keystone-players located in more regulated areas occurs resulting in a distortion of competition. There are two possible ways to establish a new regulatory framework to prevent the distortion of competition likely to be caused by the adoption of a horizontal regulatory system. First, a new ecosystem regulatory framework different from the existing one can be established. Second, the horizontal regulatory framework can be modified to reflect the ecosystem elements. The first approach is hard to adopt given the current situation as the approach requires the analysis of all broadcasting and telecommunications ecosystems including mobile and wired services; currently research and study on the competition conditions in the ecosystems is not enough. Therefore, this paper supports the second approach proposing a modified horizontal regulatory framework through the improvement of institutions and remedies suitable for accommodating the ecosystem elements. This paper intends to propose a way to regulate broadcasting and telecommunications ecosystems taking into consideration the ecosystem elements on top of the Telecommunications Business Act, Broadcasting Act, IPTV Act, the competition condition evaluation system of the Basic Act on Broadcasting and Telecommunications Development, and regulation on common carriers under the Telecommunications Business Act.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.