• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1184-1187
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• 2009

오늘날 기술 경쟁이 심화되면서 업체간 기술 격차는 큰 차이를 보이지 않고 있다. 그래서 각 기업들은 자사 제품의 경쟁력 확보를 위해 다양한 분야를 연구하게 되었고, 그 결과 소비자들에게 높은 기술력을 제공하는 것보다는 새로운 경험을 제공하는 것에 대한 중요성이 점점 부각되어 가고 있다. 그래서 본 논문에서는 PC 에서 웹 서비스(Web-Service)를 사용하는 사용자의 경험을 IPTV 에서도 경험할 수 있는 방법에 대해 연구하였고, 그 중 사용자들이 좀더 편리하고 쉽게 웹을 경험할 수 있는 Widget UI를 제안한다. 우리가 제안하는 IPTV 에서 웹 서비스를 제공하는 Widget UI 는 서로 독립적인 Widget 서비스들로 구성되어 있으며, Widget 서비스의 개수와 배치는 사용자에 따라 다르게 제공된다. 즉, 우리는 IPTV 를 위한 사용자 맞춤형 웹 서비스 제공 Widget 사용자 인터페이스를 제안한다. 또한 각 Widget 서비스의 정보 검색은 리모컨의 4 방향 키를 사용하도록 제공함으로써 사용자에게 사용의 편리성을 증대시키고 학습 피로를 감소시킬 수 있다. 이러한 학습 편의성과 사용 편리성을 사용자에게 제공함으로써 기존에 IPTV 에서 사용하기 힘들었던 웹 서비스의 사용성을 크게 향상 시키는 효과를 기대할 수 있다. 우리는 이러한 Widget UI 의 사용성을 객관적으로 평가하기 위해 UI 전문가들을 대상으로 전문가 평가를 실시하였으며, 결과 비교를 위해 다른 웹 서비스 제공 UI 들도 추가적으로 전문가 평가를 실시하였다. 전문가 평가 결과 본 논문에서 제안한 Widget UI 가 타 UI 들에 비해 높은 사용성 평가를 기록하였으며, 이 결과는 결국 우리가 제안한 Widget UI 가 IPTV 에서 웹 서비스 정보를 제공하는데 있어 효율적이고 적합한 방식임을 보여준다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.264-267
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• 2003

B2B electronic commerce of various form is gone present and e-Catalog that is used in electronic commerce is important element middle who can express well special quality of corporation's goods and product most effectively from infinite internet space. But, e-Catalog system that is used in electronic commerce is no clear concept and consistent component etc. and is constructing dissimilar system and there is shortcoming that can not use e-Catalog information exchange and transaction thereby. Propose XML(eXtensible Markup Language) in e-Catalog's standard document format to augment interoperability in selfishness species system in treatise that see hereupon, and defined e-Catalog document structure that can process goods information configurationally because using XML Schema. Also, e-Catalog registry system that offer search, registration service using e-Catalog document that is defined by XML design and embody.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.427-438
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• 2003

In a data warehouse, users typically search for trends, patterns, or unusual data behaviors by issuing queries interactively. The OLAP range-sum query is widely used in finding trends and in discovering relationships among attributes in the data warehouse. In a recent environment of enterprises, data elements in a data cube are frequently changed. The problem is that the cost of updating a prefix sum cube is very high. In this paper, we propose a novel algorithm which reduces the update cost significantly by an index structure called the Δ-tree. Also, we propose a hybrid method to provide either approximate or precise results to reduce the overall cost of queries. It is highly beneficial for various applications that need quick approximate answers rather than time consuming accurate ones, such as decision support systems. An extensive experiment shows that our method performs very efficiently on diverse dimensionalities, compared to other methods.

• Journal of the Korean Society for information Management
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• v.30 no.1
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• pp.285-302
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• 2013

This study identified topic shifts and patterns over time by analyzing an enormous amount of Twitter data whose characteristics are high accessibility and briefness. First, we extracted keywords for a certain product and used them for representing the topic network allows for intuitive understanding of keywords associated with topics by nodes and edges by co-word analysis. We conducted temporal analysis of term co-occurrence as well as topic modeling to examine the results of network analysis. In addition, the results of comparing topic shifts on Twitter with the corresponding retrieval results from newspapers confirm that Twitter makes immediate responses to news media and spreads the negative issues out quickly. Our findings may suggest that companies utilize the proposed technique to identify public's negative opinions as quickly as possible and to apply for the timely decision making and effective responses to their customers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.129-130
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• 2018

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Artificial Intelligence" keyword, one month as of May 19, 2018. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Artificial Intelligence" has been found to be technology (4,122). This study suggests theoretical implications based on the results.

• The Journal of Korean Association of Computer Education
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• v.23 no.2
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• pp.13-20
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• 2020

The interest in artificial intelligence is due to an increase in influence on companies, organizations, daily lives and society. The purpose of this study is to analyze the key elements in the teaching subjects of artificial intelligence-related subjects of Korean universities based on the intelligent system area of Computer Science 2013 in terms of human resources development. According to the analysis, there are five out of nine universities that run the required courses. Based on the 12 detailed knowledge domains of intelligent systems, the compulsory subjects of universities are distributed in the field of basic search theory, basic knowledge expression and reasoning, and inference based on uncertainty. The elective courses of each university covered topics in five to eight areas of the total knowledge area of the intelligent system, with 69.9 percent of universities with the highest average ratio of areas involving the subject of teaching subjects and 46.3 percent of universities with the lowest. This study has implications for the fact that prior to entering an artificial intelligence graduate school, we were able to grasp the level of knowledge about artificial intelligence at the undergraduate level.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.223-236
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• 2014

The paper studies the influencing factors of continuous usage intention for a scenario based cognitive FAQ service regrading on private information protection. The research result finds that three major factors are significantly positive to the continuous usage intention for the service. First, search easiness is an essential factor and it can be improved using sophisticate categorization. Second, Scenario based FAQ service is effective on understanding and solving questioner's situation. Related information is helpful for problem solving. The research shows that the new approach to private information protection area can lead to a more acceptable and reasonable problem solving tool.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.422-426
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• 2010

In recent years, multinational companies' pirate cases for traditional knowledge and genetic resources are growing. Meeting of International Authorities(MIA) agreed that traditional knowledge documentation should be included in the non-patent literature part of the Patent Cooperation Treaty(PCT) minimum documentation as a means of protection. In Korea, Korean Intellectual Property Office(KIPO) and Rural Development Administration(RDA) have played a leading role in traditional knowledge-related protection activities. KIPO's Korean Journal of Traditional Knowledge(KJTK) was selected as a PCT minimum documentation in 2008, and has been serviced through Korean Traditional Knowledge Portal(KTKP) since 2007. RDA has published several books which contain traditional agricultural knowledge and Korean local food information compiled from 1997 to now. Traditional knowledge of RDA is searchable in KTKP from 2010.In this paper, we introduce overview of activities for protection and utilization of traditional knowledge.

• Resources Recycling
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• v.17 no.4
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• pp.66-76
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• 2008

Silicon wafer is used in making semiconductor device of various forms in the semiconductor industry. Silicon wafer is produced by cutting silicon ingot and sludge containing silicon results from cutting process. The amount of silicon sludge is increasing owing to the usage of semiconductor device in many industry sectors. These days the recycling technologies of the waste silicon sludge has been widely studied from view point of economy and efficiency. In this study, patents on the recycling technologies of the waste silicon sludge were analyzed. The range of search was limited in the open patents of USA, European Union, Japan, and Korea up to september, 2007. Patents were collected using key-words and filtered by filtering criteria. The trend of the patents was analyzed by the years, countries, companies, and technologies.

• Journal of KIISE
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• v.45 no.3
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• pp.294-302
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• 2018

With the emergence of the new service industry due to the development of information and communication technology, cyber space risks such as personal information infringement and industrial confidentiality leakage have diversified, and the security problem has emerged as a critical issue. In this paper, we propose a behavior-based anomaly detection method that is suitable for real-time and large-volume data analysis technology. We show that the proposed detection method is superior to existing signature security countermeasures that are based on large-capacity user log data according to in-company personal information abuse and internal information leakage. As the proposed behavior-based anomaly detection method requires a technique for processing large amounts of data, a real-time search engine is used, called Elasticsearch, which is based on an inverted index. In addition, statistical based frequency analysis and preprocessing were performed for data analysis, and the DBSCAN algorithm, which is a density based clustering method, was applied to classify abnormal data with an example for easy analysis through visualization. Unlike the existing anomaly detection system, the proposed behavior-based anomaly detection technique is promising as it enables anomaly detection analysis without the need to set the threshold value separately, and was proposed from a statistical perspective.