• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.172-178
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• 2020

In order to recommend contents, the company generally uses collaborative filtering that takes into account both user preferences and video (item) similarities. Such services are primarily intended to facilitate user convenience by leveraging personal preferences such as user search keywords and viewing time. It will also be ranked around the keywords specified in the video. However, there is a limit to analyzing video similarities using limited keywords. In such cases, the problem becomes serious if the specified keyword does not properly reflect the item. In this paper, I would like to propose a system that identifies the characteristics of a video as it is by the system without human intervention, and analyzes and recommends similarities between videos. The proposed system analyzes similarities by taking into account all words (keywords) that have different meanings from training videos, and in such cases, the methods handled by big data clusters are applied because of the large scale of data and operations.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.489-495
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• 2018

The purpose of this study was to investigate the effect of fouls on performance in field hockey games. A total of 33 matches and 2101 fouls from 10 teams participated in the 2017 World League SEMI-FINAL tournament were analysed by region, race, type, and cause. The total data that is analysed by SportsCode and SPSS(correlation analysis & chi-square test)have showed that the top ranked countries had a higher foul frequency than the lower ranked nations. According to the situation that has showed the result of the analysis, it showed that there was no difference between the results analysed on the foul type and the attacking and defence situation but it has indicated that area, game situation and the cause of fouls showed there was a significant difference. On these results, it is hoped to use fouls as one of the tactical means in women's field hockey games.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.61-76
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• 2015

In general, we have utilized the hierarchical concept tree as a crucial data structure for indexing huge amount of textual data. This paper proposes a generality rank-based method that can automatically develop hierarchical concept structures with the Wikipedia data. The goal of the method is to regard each of Wikipedia articles as a concept and to generate hierarchical relationships among concepts. In order to estimate the generality of concepts, we have devised a special ranking function that mainly uses the number of hyperlinks among Wikipedia articles. The ranking function is effectively used for computing the probabilistic subsumption among concepts, which allows to generate relatively more stable hierarchical structures. Eventually, a set of concept pairs with hierarchical relationship is visualized as a DAG (directed acyclic graph). Through the empirical analysis using the concept hierarchy of Open Directory Project, we proved that the proposed method outperforms a representative baseline method and it can automatically extract concept hierarchies with high accuracy.

• The Journal of Korean Association of Computer Education
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• v.20 no.1
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• pp.13-26
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• 2017

The programming(algorithm) automated assessment system is to evaluate automatically the accuracy and time/space efficiency of user's solution to the problem which is provided. This system gives the immediate feedback of the solution, real-time ranking. So, in the course of data structure and algorithm, we can apply the knowledge which we have learned to the problem solving. Especially, in the basic course of learning the syntax of the programming language, the novice student can learn in easy and fun by solving the simple problem. The university students can understand in the easy way the meaning of asymptotic analysis of algorithm in data structure & algorithm course.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.620-628
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• 2010

With the use of the Internet pervasive in everyday life, people are now able to retrieve a lot of information through the web. However, exponential growth in the quantity of information on the web has brought limits to online search engines in their search performance by showing piles and piles of unwanted information. With so much unwanted information, web users nowadays need more time and efforts than in the past to search for needed information. This paper suggests a method of using query expansion in order to quickly bring wanted information to web users. Popularity based Term Weight Mensuration better performance than the TF-IDF and Simple Popularity Term Weight Mensuration to experiments without changes of search subject. When a subject changed during search, Popularity based Term Weight Mensuration's performance change is smaller than others.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.240-254
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• 2018

This study investigated the antecedents of web-drama success as the interests on web-drama is increasing. We focused on the factors which help web-drama success because current studies on web-drama has focused on the description of market. We examined the effect of fandom on the success of web-drama using the data of constv site which provided with the rank (1-100) of web-drama between February 1st and March 1st in 2016. We found that the fandom had a positive effect on the success of web drama. In addition, we also found that the number of people registered in web-drama channel mediated the relationship between the fandom and the success of web-drama. This study contributed to the current literature by revealing the factors which enable the success of web-drama.

• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.492-497
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• 2014

In this paper, we propose a method of retrieving opinioned tweets in Twitter, which is the one of the popular Social Network Services and shares diverse opinions among various users. In typical opinion retrieval systems, they may consider the presence of sentiment phrases (subjectivity) as the important factor even if the subjective phrases are not related to a given query or speaker. To alleviate these problems, we utilized the syntactic structure of a sentence to identify the relationships between 1) subjectivity-query and 2) subjectivity-speaker and 3) the syntactic role of subjectivity. Besides, our learning-to-rank approach is trained to retrieve opinioned tweets based on query-relevance, textual features, user information, and Twitter-specific features. Experimental results on real world data show that our proposed method can achieve better performance than several baseline methods in terms of precision and nDCG.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.89-92
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• 2013

South Korea's advertising market in 2012, growing at a standard 10 trillion, but most advertising is in the form of one-way communication by advertisers. In this paper, at the time they are attracting the interest of consumers, more recent placement by Facebook or Youtube propose an advertising platform using the Kinect motion-sensitive controller that can communicate with consumers. In the proposed platform, by the simple enjoyment of the game accept ads without resistance, and can deliver content more effectively than advertising indirectly passing. Had occurred in the existing Windows forms drawing problem was solved by using the XNA game engine using the Facebook API was designed so that it can be integrated with SNS.The scored elements to attract the interest of the users with the introduction of the ranking system and the user's face image to extract added to the story line, and increased immersive.

• Journal of Information Technology and Architecture
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• v.9 no.3
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• pp.323-331
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• 2012

With the advancement of the area of knowledge and information, Intellectual Property, especially, patents have captured attention more and more emergent. The increasing need for efficient way of patent information search has been essential, but the prevailing patent search engines have included too many noises for the results due to the Boolean models. This has occasioned too much time for the professional experts to investigate the results manually. In this paper, we reveal the differences between the conventional document search and patent search and analyze the limitations of existing patent search. Furthermore, we propose a specialized in patent search, so that the relationship between the keywords within each document and their significance within each patent document search keyword can be identified. Which in turn, the keywords and the relationships have been appointed a ranking for this patent in the upper ranks and the noise in the data sub-ranked. Therefore this approach is proposed to significantly reduce noise ratio of the data from the search results. Finally, in, we demonstrate the superiority of the proposed methodology by comparing the Kipris dataset.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.79-82
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• 2019

This study aims to design and implement automated SEO tools that has applied the artificial intelligence techniques for search engine optimization (SEO; Search Engine Optimization). Traditional Search Engine Optimization (SEO) on-page optimization show limitations that rely only on knowledge of webpage administrators. Thereby, this paper proposes the metadata generation system. It introduces three approaches for recommending metadata; i) Downloading the metadata which is the top of webpage ii) Generating terms which is high relevance by using bi-directional Long Short Term Memory (LSTM) based on attention; iii) Learning through the Generative Adversarial Network (GAN) to enhance overall performance. It is expected to be useful as an optimizing tool that can be evaluated and improve the online marketing processes.