• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.223-228
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• 2023

According to the Korea Information Society Development Institute, OTT services grew at a rate of 33.4% in four yearsfrom 2017, when they were first launched.TheKorea Export-Import Bank announced in 2020 that the domestic OTT market was worth 780.1 billionKRW. This growth of the OTT market is expected to stimulate competition among OTT service platforms, and user satisfactionwithconvenience features, such as video recommendations, seems to be acting as an important factor in the competition.Currently, the OTT market uses a variety ofdata for customized recommendations, but the limitationis that it only uses datacollected within the app. Thereby we have proposed the use ofpersonal data collected outside the app for personalized recommendations, and the survey results showed that user satisfaction was 23.72% higher for recommended content based on the proposedmethod thanNetflix recommended content.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.1-7
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• 2020

As the demand for health screening increases, there is a need for efficient design of screening items. We build machine learning models for health screening and recommend screening items to provide personalized health care service. When offline, a synthetic data set is generated based on guidelines and clinical results from institutions, and a machine learning model for each screening item is generated. When online, the recommendation server provides a recommendation list of screening items in real time using the customer's health condition and machine learning models. As a result of the performance analysis, the accuracy of the learning model was close to 100%, and server response time was less than 1 second to serve 1,000 users simultaneously. This paper provides an adaptive and automatic recommendation in response to changes in the new screening environment.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.675-678
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• 2006

IPTV (Internet Protocol Television) is an efficient system which serves various contents to subscribing consumers by using the IP over a broadband connection. The IPTV services can be multi-channel broadcasting service, VoD, T-Commerce, video conference, on-line game and so on. TV Anytime metadata provides various description tools for TV program contents by which TV program contents can serve more information. In this paper, we mention about the overview and feature of IPTV and TV Anytime metadata, propose the essential functions in the EPG program of IPTV and survey the description tools for the proposed functions in EPG. Finally, we show the authored metadata and the implementation of advanced EPG application.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.62-74
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• 2021

We compare Over-the-Tops (OTTs), Netflix and Amazon Prime Video (APV) with five success factors of innovation. Firstly, Netflix offers better personalized service than APV, because APV has collaborative filtering algorithms to recommend safe bets, not the customers really want. Secondly, APV' user interface is undercooked to lock the members in, even if it has more content and better price offer than Netflix retaining its loyal customers despite the price increase. Thirdly, Netflix has simple subscription model with three tiering, but APV has complicated pricing model having annual and monthly, APV and Prime Video (AV) app, Amazon subscription and extra payment of Amazon Prime Channels (APCs). Fourthly, Amazon has fewer partnership than Netflix especially when it comes to local TV series. Instead, Amazon has live TV channel collaboration including sports content. Lastly, both have strategic and operational agility in their organization well.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.122-128
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• 2024

This study delves into the unique transformation of South Korea's elderly population, distinctively termed 'Nomad Silver'. Characterized by individuals aged 65 and above who actively seek novel experiences and embrace new activities, this demographic shift signifies a departure from traditional perceptions of the elderly. The Nomad Silver cohort, distinguished by their significant economic influence and evolving needs, necessitates a tailored approach to healthcare services. This paper underscores the importance of comprehending both the fundamental biological needs and the personalized desires of the Nomad Silver, aiming to enhance their satisfaction and overall well-being. Hospitals, in response, should innovate their services to resonate with the emotional, psychological, and social facets of this age group. Consequently, the paper proposes a four-pronged strategy for hospitals to adapt: comprehensive healthcare provision, patient-centric service development, senior health education coupled with community engagement, and establishing a generational bridge hub. Furthermore, the paper posits that catering to the Nomad Silver not only promises substantial financial gains for hospitals but also fosters new business opportunities across various sectors.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.355-362
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• 2011

Since two-way interactive broadcasting service began, remote controls have been fitted with 4 color buttons, which enables interaction and convenience to increase between users and content. Currently, diverse studies on IPTV are in progress. Particularly, as the mobile market rapidly grows, studies on mobile IPTV and on linkage with other media are constantly increasing. However, mobile IPTV has never been studied until now. In that sense, this present study attempted to design a mobile-based IPTV UI that could use a multi-dimensional search method based on consistent criteria for content search. As a result, the proposed IPTV UI is fitted with more usability and functionality for 4 color buttons. The UI designed in this study was compared to the IMDb Android Application, which uses GOMS-KLM. The results showed that the performance process was reduced by three stages, and that the performance time was reduced by more than 17.9%. Therefore, the conclusion can be reached that the proposed UI is effective for a fast search of contents.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.758-769
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• 2020

Hybrid broadcasts utilizing heterogeneous networks can provide not only uniform broadcasting services but also various services using broadcast networks and communication networks. In particular, as content is consumed in various countries and regions, demands for personalized services continue to increase, and research on content insertion technology utilizing heterogeneous networks has been actively conducted. The most important technical challenge when inserting content based on heterogeneous networks is that the start of the inserted content, which replaces the original broadcast content at the time of content insertion, should proceed smoothly, and it must be able to accurately return to the original broadcast content. Currently, UHD broadcasting is converted to digital. However, since there is a system that supports the frame rate used in the analog method, when content insertion occurs in a conventional UHD broadcasting service, there is a problem in decoding the broadcast and inserted content. Since the replacement cost of the broadcasting system is astronomical, this paper proposes a content insertion method using by frame control that can support analog methods without replacing transmission equipment.

• Journal of KIISE
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• v.44 no.5
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• pp.545-552
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• 2017

Because of the explosive growth of mobile devices and development of network technologies, HTTP (Hypertext Transfer Protocol) adaptive streaming has become a new trend in video delivery to provide efficient multimedia streaming services. As interest in personalized broadcasting grows, the study of interactive multimedia has been actively pursued. The interactive multimedia service is a method of playing media according to a scenario selected by the user. Providing the interactive multimedia service with the existing HTTP adaptive streaming causes switching delay and buffer underflow according to the point in time when the user selects the scenario while the client streams the interactive multimedia and therefore decreases the user QoE (Quality of Experience). In this paper, we propose an adaptive streaming scheme for interactive multimedia service in HTTP adaptive streaming to provide seamless playback. We design the architecture and prefetching scheme for interactive multimedia streaming.