• Journal of the Korean BIBLIA Society for library and Information Science
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• v.17 no.2
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• pp.239-259
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• 2006

The purpose of this study is to propose some strategic directions which can promote the government libraries to provide the most effective and efficient information services. The study analyzes user opinion and demand in terms of the Web-based Information Services. For the analysis, the questionnaires were distributed to the 300 users in 18 government libraries. In the results, the study finds that the government libraries with homepage need to advertise homepage service. to provide the training programs, and to improve the system utility for better valuable homepage services. The government libraries without homepage, first of all, must construct their own homepage reflected in the users demand requiring the powerful retrieval ability, the diversity of contents, the high properness of information services.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.1-9
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• 2010

In the new generation of Web, commonly called "Web 2.0", blogging has facilitated the publishing information or his/her opinion on the web. Various blog retrieval algorithms have been proposed to search for blogs more effectively. However, actually keyword-based searching or link-analysis blog ranking system cannot satisfy the user's requirement. In this paper, we suggest a topic-based weighting blog retrieval system in which the links between blog writings and searching words are considered to improve the search results. Our system extracts topics from each blog and weights them much higher than other guide words. In the comparison with other systems, we see that the proposed topic-base system has better recall rate of search results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.141-148
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• 2015

This paper proposes the BDAS(Big Data analysis Scheme) design that extracts the real time shared information from SNS and Web, analyzes the extracted data rapidly for customers, and makes an on-line marketing strategy efficiently. First, the BDAS collects the data shared in SNS and Web. Second, it provides the result of visualization by analyzing the semantics of the collected data as positive or negative. Therefore, because the BDAS ensures an average 90% accuracy in judging the semantics about the shared SNA and Web data, it can judge customer's propensity accurately and be used for on-line marketing strategy efficiently.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.899-911
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• 2005

This paper conducts an explanatory analysis of the web sphere produced by National Assemblymen in South Korea, using some statistical methods. First, some descriptive metrics were employed. Next, the traditional methods of multi-variate analyses, multidimensional scaling and corresponding analysis, were applied to the data. Finally, cross-sectional data were compared to examine a change over time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.85-89
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• 2008

웹상에서 자동 데이터 추출과 분석기법은 최근 검색분야의 주요이슈이다. 본 논문은 웹상의 자동 설문조사 시스템에 관한 연구이다. 그리고 기존의 Corpus의 성향을 분석하고 검색 및 분석 시스템의 항목들을 정의하였다. 또한 Corpus를 이용한 웹 검색 및 분석 시스템의 활용 분야를 기술하고 향후 개발 방향을 기술하였다.

• The Journal of Information Systems
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• v.20 no.2
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• pp.21-36
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• 2011

The Web has become an excellent source for gathering consumer opinions. There are now numerous Web sites containing such opinions, e.g., customer reviews of products, forums, discussion groups, and blogs. This paper focuses on online customer reviews of products. It makes some contributions. Especially it proposes minimalism and chunking framework for analyzing and comparing consumer opinions of competing products. Users are able to clearly see the strengths and weaknesses of each product in the minds of consumers in terms of various product features. This comparison is useful to both potential customers and product manufacturers. For a product manufacturer, the comparison enables it to easily gather marketing intelligence and product benchmarking information. In this paper, we only focus on mining opinion/product features that the reviewers have commented on. Five types of online review presentations are presented to mine such features. Our experimental results show that these techniques are useful to identify customers' opinions and trends.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.318-325
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• 2010

In this study, the wrapper database description language and model is suggested to collect product reviews from Korean shopping malls with multi-layer structures and are built in a variety of web languages. Above all, the wrapper based web crawlers have the website structure information to bring the exact desired data. The previously suggested wrapper based web crawler can collect HTML documents and the hierarchical structure of the target documents were only 2-3 layers. However, the Korean shopping malls in the study consist of not only HTML documents but also of various web language (JavaScript, Flash, and AJAX), and have a 5-layer hierarchical structure. A web crawler should have information about the review pages in order to visit the pages without visiting any non-review pages. The proposed wrapper contains the location information of review pages. We also propose a language grammar used in describing the location information.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.1-11
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• 2020

Through text mining, sentiment analysis, and semiotics analysis, this study aims to reinterpret the meaning of user emotional words and related words to derive strategic elements of brand and design. After selecting a local car manufacturer whose user opinion on the brand is a clear topic, web-crawl the car comments of the manufacturer directly created by the users online. Then, analyze the extracted morphology and its associated words and convert them to fit the marketing mix theory. Through this process, propose a methodology that allows consumers to supplement and improve brand elements with negative sensibilities, and to inherit elements with positive sensibilities and manage brands reasonably. In particular, the Map presented in this study are considered to be fully utilized as information for overall brand management.

• International Journal of Advanced Culture Technology
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• v.9 no.2
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• pp.86-90
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• 2021

Sentiment refers to a person's thoughts, opinions, and feelings toward an object. Sentiment analysis is a process of collecting opinions on a specific target and classifying them according to their emotions, and applies to opinion mining that analyzes product reviews and reviews on the web. Companies and users can grasp the opinions of public opinion and come up with a way to do so. Recently, natural language processing models using the Transformer structure have appeared, and Google's BERT is a representative example. Afterwards, various models came out by remodeling the BERT. Among them, the Facebook AI team unveiled the XLM-R (XLM-RoBERTa), an upgraded XLM model. XLM-R solved the data limitation and the curse of multilinguality by training XLM with 2TB or more refined CC (CommonCrawl), not Wikipedia data. This model showed that the multilingual model has similar performance to the single language model when it is trained by adjusting the size of the model and the data required for training. Therefore, in this paper, we study the improvement of Korean sentiment analysis performed using a pre-trained XLM-R model that solved curse of multilinguality and improved performance.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.63-84
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• 2020

With the recent announcement of the WCAG2.2 Work Draft of the W3C, revision of the WCAG2.2 guidelines will be made soon. Consequently, the revision of KWCAG2.1 in response to changes in the domestic and international environment of web accessibility is urgent. The revision primarily involves development and selection of web accessibility evaluation items. In this study, the efficient procedures and useful methodologies for developing and selecting the evaluation items are to be presented. FGI (Focus Group Interview) has been devised to reflect every stakeholders opinion fairly. GT (Group Technology) has been applied to expedite the revision processes particularly in the FGI. QFD (Quality Function Deployment) method plays an important role in investigating the relationship between evaluation items and its characteristics, and in analyzing the importance and priorities of each item. This study proposes 5 principles, 17 guidelines and 39 evaluation items which can be used for the revision of KWCAG 2.1. This study is expected to be of great help in establishing the KWCAG 2.2 in the near future.