• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.348-353
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• 2004

Development of an efficient and secure payment system is prerequisite for the construction of electronic payment mechanism in mobile environment. Since current PayWord protocol system generates vendor's certificate for each transaction, it requires lot of operation for transaction. In this paper, we use a session key generated by ID-based tripartite Key agreement protocol which use an Elliptic Curve Cryptosystem over finite field $F_{q}$ for transactions. Therefore, our protocol reduces algorithm operations. In particular, proposed protocol using ID-based public key cryptosystem has the advantages over the existing systems in speed and it is more secure in Man-in-the-middle attacks and Forward secrecy.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1586-1593
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• 2010

Vocabulary recognition error correction method has probabilistic pattern matting and dynamic pattern matting. In it's a sentences to based on key-word by semantic analysis. Therefore it has problem with key-word not semantic analysis for morphological changes shape. Recognition rate improve of vocabulary unrecognized reduced this paper is propose. In syllable restoration algorithm find out semantic of a phoneme recognized by a phoneme semantic analysis process. Using to sentences restoration that morphological analysis and morphological analysis. Find out error correction rate using phoneme likelihood and confidence for system parse. When vocabulary recognition perform error correction for error proved vocabulary. system performance comparison as a result of recognition improve represent 2.0% by method using error pattern learning and error pattern matting, vocabulary mean pattern base on method.

• Journal of KIISE:Information Networking
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• v.31 no.4
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• pp.405-413
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• 2004

Design an efficient and secure electronic payment system is important for M-Commerce. In this paper, we propose an efficient Micro-Payment Protocol that allows multiple transactions using ID-based public key cryptosystem. Current PayWord system requires to generate certificate of the vendor for each transaction. In this paper, we use a session key instead of certificate key generated by Weil Pairing which use an Elliptic Curve Cryptosystem over finite field $F_q$ for transactions Therefore, it is more secure in Known key attacks as well as Man-in-the-middle attacks.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.57-60
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• 2000

Even if the video data is utilized for a lot of field, its very difficult to reuse and search easily because of its atypical(unfixed form) and complicated structure. In this study, we presented the video retrieval system which is based on the synchronized closed caption and video, SMIL and SAMI languages which are described to structured and systematic form like multimedia data These have next structure; At first, a key word is inputted by user, then time stamp would be sampling from the string which has a key word in the caption file. To the result, the screen shows an appropriate video frame.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.17-27
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• 2012

Open Market is one of the key factors to accelerate the profit. Usually retailers sell items in several Open Market. One of the challenges for retailers is to assign categories of items with different classification systems. In this research, we propose an item category recommendation method to support appropriate products category registration. Our recommendations are based on semantic relation between existing and any other Open Market categorization. In order to analyze correlations of categories, we use Morpheme analysis, Korean Wiki Dictionary, WordNet and Google Translation API. Our proposed method recommends a category, which is most similar to a guide word by measuring semantic similarity. The experimental results show that, our system improves the system accuracy in term of search category, and retailers can easily select the appropriate categories from our proposed method.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.199-206
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• 2003

one of the representative micropayment protocols. The original PayWord system is designed for a user who generates paywords by performing hash chain operation for payment to an only designated vendor. In other words, a user has to create new hash chain values in order to establish commercial transactions with different vendors on the Internet. Therefore, we suggest an efficient scheme that is able to deal with business to different vendors by using only one hash chain operation to supplement this drawback. In this proposed system, a broker creates a new series of hash chain values along with a certificate for the user's certificate request. This certificate is signed by a broker to give authority enabling a user to generate hash chain values. hew hash chain values generated by a broker provide means to a user to do business with multiple vendors.

• Journal of Internet Computing and Services
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• v.2 no.1
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• pp.49-61
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• 2001

Internet has been becoming widely popular and making rapid progress and network technologies is showing extension in data transmission speeds. Rapid and convenient multimedia services supplied with high quality and high speed are being needed, This paper treats of the design and implement method of clip-based video retrieval system on the world-wide-web environments. The implemented system consists of the content-based indexing system supporting convenient services for video contents providers and the web-based retrieval system in order to make it easy and various information retrieval for users on the world-wide-web. Three important methods were used in the content-based indexing system. Key frame extracting method by dividing video data, clip file creation method by clustering related information and video database build method by using clip unit, In web-based retrieval system, retrieval method by using a key word, two dimension browsing method of key frame and real-time display method of the clip were used. As a result. the proposed methodologies showed a usefulness of video content providing. and provided an easy method for searching intented video content.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• The KIPS Transactions:PartC
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• v.8C no.1
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• pp.75-87
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• 2001

The Conditional Access System is the complete system for ensuring that broadcasting services are only accessible to those who are entitled to receive them. Four major parts to this system are scrambling, descrambling, authentication and encryption. For the proper operation, which means hard-to- break and uninterrupted service, secure key management and efficient delivery mechanism are very important design factors to this system. Performance analysis is another important factor to this system that is used in massive subscriber environment. In this thesis, one of the secure and efficient key management mechanisms is proposed. For the secrecy of this mechanism, hierarchical stacking of keys and key generation matrix are proposed. For the proof of efficient delivery of those keys, simulation results and performance analysis. which is based on queuing analysis, are presented. Lastly, optimal key generation and delivery period, maximal and minimal key deliver time, and communication capacity for data collection are presented for various subscriber volume.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.123-141
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• 2019

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.