• Journal of the Korean Society for Library and Information Science
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• v.36 no.4
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• pp.175-205
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• 2002

Information visualization in information retrieval is a creating tool that enables us to observe, manipulate, search, navigate, explore, filter, discover, understand, interact with large volumes of data for more rapidly and far more effectively to discover hidden patterns. The focus of this study is to investigate and analyze information visualization techniques in information retrieval system in the three-schematic levels. In result, it was found that first, scientific data, documents, and retrieval result information are visualized through various techniques. Second, information visualization techniques which facilitate navigation and interaction are zoom and pan, focus+context techniques, incremental exploration, and clustering. Third, the visual metaphors used by the visualization systems are presented in the linear structure, hierarchy structure, network structure, and vector scatter structure.

• The Journal of the Korea Contents Association
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• v.7 no.5
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• pp.16-26
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• 2007

Because it is difficult on existing document retrieval systems to visualize the search result, search results show document titles and short summaries of the parts that include the search keywords. If the result list is long, it is difficult to examine all the documents at once and to find a relation among them. This study uses clustering to classify similar documents into groups to make it easy to grasp the relations among the searched documents. Also, this study proposes a two-level visualization algorithm such that, first, the center of clusters is projected to low-dimensional space by using multi-dimensional scaling to help searchers grasp the relation among clusters at a glance, and second, individual documents are drawn in low-dimensional space based on the center of clusters using the orbital model as a basis to easily confirm similarities among individual documents. This study is tested on the benchmark data and the real data, and it shows that it is possible to visualize search results in real time.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.91-104
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• 2016

Business intelligence based on the data analysis come into the spotlight. Especially, information visualization of the analysis result is treated significantly. given the interest in big data technologies. Because corporate managers want to use the results of data analysis in the decision-making process and the visualization technology will give help with cognitive function and operation function. In this paper, the status of information visualization is reviewed and analyzed from the viewpoint of manufacturing service. Several implications are drawn and it is expected that they will help to developers and administrators of manufacturing sector who want to adopt information visualization applications.

• Journal of the Korean Society for Library and Information Science
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• v.41 no.3
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• pp.181-199
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• 2007

This study is to suggest the usefulness of visualization techniques to display web retrieval results. We described the concept of visualization techniques and evaluated the usability for the SearchCrystal and KartOO search engines which provide visualization techniques for displaying the retrieval results. As a result, Searchcrystal search engine had higher score than KartOO system in terms of usability check lists.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.225-249
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• 2024

The purpose of this study is to develop an evaluation tool for map-based data visualization platforms and to conduct heuristic usability evaluations on existing platforms representing inter-regional information. We compared and analyzed the usability evaluation criteria of map-based platforms from the previous studies along with Nielsen's (1994) 10 usability evaluation principles. We proposed nine evaluation criteria, including (1) visibility, (2) representation of the real world, (3) consistency and standards, (4) user control and friendliness, (5) flexibility, (6) design, (7) compatibility, (8) error prevention and handling, and (9) help provision and documentation. Additionally, to confirm the effectiveness of the proposed criteria, four experts was invited to evaluate five domestic and international map-based data visualization platforms. As a result, the experts were able to rank the usability of the five platforms using the proposed map-based data visualization usability evaluation criteria, which included quantified scores and subjective opinions. The results of this study are expected to serve as foundational material for the future development and evaluation of map-based visualization platforms.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.2
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• pp.287-304
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• 2005

The goal of this research is to evaluate the usability of visually browsing the automatically extracted information. A domain-independent information extraction system was used to extract information from news type texts to populate the visually browasable knowledge base. The information extraction system automatically generated Concept-Relation-Concept triples by applying various Natural Language Processing techniques to the text portion of the news articles. To visualize the information stored in the knowledge base, we used PersoanlBrain to develop a visualization portion of the user interface. PersonalBrain is a hyperbolic information visualization system, which enables the users to link information into a network of logical associations. To understand the usability of the visually browsable knowledge base, IS test subjects were observed while they use the visual interface and also interviewed afterward. By applying a qualitative test data analysis method. a number of usability Problems and further research directions were identified.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.183-196
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• 2016

The academic journal is an important medium carrying newly discovered knowledge in various disciplines. It is desirable to consider visualization of journal and article information in order to make the information more insightful and effective than text-based information. In this study, visualization service platform of journal and article information is developed. TagCloud were included in both Infographics of journal and article. Each word in the TagCloud is inter-linked with DBPedia using Linked Open Data (LOD) technique.

• Proceedings of the Korean Society for Information Management Conference
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• 2016.08a
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• pp.97-100
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• 2016

본 연구는 기초학문자료센터의 연구데이터를 후속연구자들이 효율적으로 이용하며 연구데이터의 재이용을 향상시키기 위한 시각화 서비스를 제시하고자 한다. 이를 위하여 기초학문자료센터를 이용한 경험이 있는 연구자를 인터뷰하여 현재 기초학문자료센터의 미비점과 개선점을 파악하고, 시각화가 필요한 부분에 대한 의견을 수집하였다. 조사 결과, 기초학문자료센터에서 제공하는 연구성과물이 양적으로 부족하며, 통합검색을 제외한 연구과제 검색, 연구성과물유형별 검색, 연구분야분류별 검색은 불필요하고, 추천검색어가 보완될 필요가 있었다.

• The Journal of Bigdata
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• v.5 no.1
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• pp.77-88
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• 2020

Recently, many researches habe been done to organize and analyze various complex relationships in real world, represented in the form of graphs. In particular, the computer field literature data system, such as DBLP, is a representative graph data in which can be composed of papers, their authors, and citation among papers. Becasue graph data is very complex in storage structure and expression, it is very difficult task to search, analysis, and visualize a large size of bibliographic big data. In this paper, we develop a graphic user interface tool, called EEUM, which visualizes bibliographic big data in the form of graphs. EEUM provides the features to browse bibliographic big data according to the connected graph structure by visually displaying graph data, and implements search, management and analysis of the bibliographc big data. It also shows that EEUM can be conveniently used to search, explore, and analyze by applying EEUM to the bibliographic graph big data provided by DBLP. Through EEUM, you can easily find influential authors or papers in every research fields, and conveniently use it as a search and analysis tool for complex bibliographc big data, such as giving you a glimpse of all the relationships between several authors and papers.

• Journal of Information Management
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• v.42 no.2
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• pp.85-102
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• 2011

Conventionally, scientific data visualization is thought of as one of activities performed by scientists during the scientific data analysis. However, recently, there exits a set of research papers which count scientific data visualization as a independent research area. They show the research subjects for studying the scientific data visualization technology and methods. In case, a scientist or group of scientists can not solve their own visualization problem due to the unskillfulness and inexperience on using visualization tool. Therefore, it needs to help them by the systematic way for solving the problem. In this study, we analyze and propose the national level scientific visualization support system for scientists. In particular, we first analyze the existing papers and find out the critical success factors. Then, by integrating the findings of the analysis, we propose the research areas which need to be focused, and the strategic direction and specific research topics for scientific data visualization support system in national level.