• Journal of dental hygiene science
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• v.18 no.6
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• pp.380-388
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• 2018

This research team extracted keywords from 953 papers published in the Journal of Dental Hygiene Science from 2001 to 2018 for keyword and centrality analyses using the Keyword Network Analysis method. Data were analyzed using Excel 2016 and NetMiner Version 4.4.1. By conducting a deeper analysis between keywords by overall keyword and time frame, we arrived at the following conclusions. For the 17 years considered for this study, the most frequently used words in a dental science paper were "Health," "Oral," "Hygiene," and "Hygienist." The words that form the center by connecting major words in the Journal of Dental Hygiene through the upper-degree centrality words were "Health," "Dental," "Oral," "Hygiene," and "Hygienist." The upper betweenness centrality words were "Dental," "Health," "Oral," "Hygiene," and "Student." Analysis results of the degree centrality words per period revealed "Health" (0.227), "Dental" (0.136), and "Hygiene" (0.136) for period 1; "Health" (0.242), "Dental" (0.177), and "Hygiene" (0.113) for period 2; "Health" (0.200), "Dental" (0.176), and "Oral" (0.082) for period 3; and "Dental" (0.235), "Health" (0.206), and "Oral" (0.147) for period 4. Analysis results of the betweenness centrality words per period revealed "Oral" (0.281) and "Health" (0.199) for period 1; "Dental" (0.205) and "Health" (0.169) for period 2, with the weight then dispersing to "Hygiene" (0.112), "Hygienist" (0.054), and "Oral" (0.053); "Health" (0.258) and "Dental" (0.246) for period 3; and "Oral" (0.364), "Health" (0.353), and "Dental" (0.333) for period 4. Based on the above results, we hope that further studies will be conducted in the future with diverse study subjects.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.111-120
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• 2015

Protein named entity identification is one of the most essential and fundamental predecessor for extracting information about protein-protein interactions from biomedical literature. In this paper, we explore the use of abstracts of biomedical literature in MEDLINE for protein name identification and present the results of the conducted experiments. We present a robust and effective approach to classify biomedical named entities into protein and non-protein classes, based on a rich set of features: orthographic, keyword, morphological and newly introduced Protein-Score features. Our procedure shows significant performance in the experiments on GENIA corpus using Random Forest, achieving the highest values of precision 92.7%, recall 91.7%, and F-measure 92.2% for protein identification, while reducing the training and testing time significantly.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.1
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• pp.89-98
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• 2009

The existing mashup service providers have induced users to participate in their own made services and have grown their services by user participations and contributing contents. Recent services based on Web2.0 are called by 'Open (Content) Service' which means anyone can provide new services to the others without any of their own contents. But unfortunately the most of these days services are not opened. They just using mashups for increasing their service's traffics. We introduce the way to make a simple service to provide searching videos present it with extracted keyword from external content without our own contents at all. this show that how to combine the content with another contents or services.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.131-146
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• 2012

The purpose of this research is two-fold : (1) we propose the paradigm to construct a connected information society according to a judgment where a coming information society will evolve into highly-connected information society having "seamlessness" as a keyword, and (2) we draw guidelines to construct infrastructures and establish systems and business models of highly-connected information society based on suggested paradigm. To achieve this, this research conducts the followings. First, we suggest reasons why a coming information society can be appropriate to be considered as highly-connected information society by examining two perspectives on the coming information society. Second, we explain the definition and characteristics of highly-connected information society and propose the SPB paradigm. Third, we analyze the utility of SPB paradigm by evaluating practices. Finally, we suggest four strategies to construct highly-connected information society based on advanced research findings and future research directions.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1951-1952
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• 2006

To effectively deal with video data, a semantic-based retrieval scheme that allows for processing diverse user queries and saving them on the database is required. In this regard, this paper proposes a semantic-based video retrieval system that allows the user to search diverse meanings of video data for electrical safetyrelated educational purposes by means of automatic annotation processing. If the user inputs a keyword to search video data for electrical safety-related educational purposes, the mobile agent of the proposed system extracts the features of the video data that are afterwards learned in a continuous manner, and detailed information on electrical safety education is saved on the database. The proposed system is designed to enhance video data retrieval efficiency for electrical safety-related educational purposes.

• The Journal of Information Systems
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• v.18 no.3
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• pp.327-349
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• 2009

Traditional keyword-based searching methods suffer from low accuracy and high complexity due to the rapid growth in the amount of information. Accordingly, many researchers attempt to implement a so-called semantic search which is based on the semantics of the user's query. Semantic information can be described using a semantic modeling language, such as Topic Map. In this paper, we propose a new method to map a topic map to a traditional Relational Database (RDB) without any information loss. Although there have been a few attempts to map topic maps to RDB, they have paid scant attention to handling multi-role topics. In this paper, we propose a new storage structure to map multi-role topics to traditional RDB. The proposed structure consists of a mapping table, role tables, and content tables. Additionally, we devise a query translator to convert a user's query to one appropriate to the proposed structure.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.596-605
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• 2005

Conventional XML query methods such as simple keyword match or structural query expansion are not sufficient to catch the underlying information in the documents. Moreover, these methods inefficiently try to query all the documents. This paper proposes document tittering and query expansion methods that are based on ontology. Using ontology, we construct a universal DTD that can filter off unnecessary documents. Then, query expansion method is developed through the analysis of concept hierarchy and association among concepts. The proposed methods are applied on variety of sample XML documents to test the effectiveness.

• Proceedings of the CALSEC Conference
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• 2001.08a
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• pp.625-629
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• 2001

A cyber shopping mall is a place where consumers acquire product information, and make purchase decisions in the cyber space. Even though it offers many advantages over traditional malls, there are still several limitations to do shopping in an existing cyber mall. One of these limitations is the absence of an efficient shopping aid to compare multiple items from multiple malls. Existing search systems usually support a keyword search with limited conditions. Consumers spend lots of their time to compare multiple alternatives from search results. In this paper, we propose an intelligent product search system. There are two main features in our system. The first one is a full support of comparison shopping with multiple perspectives based on commercial search engines. The second one is an enhancement to the shopping aid based on a new concept of Shopping AssistanT. Our system is implemented in Visual Basic and PERL, and experimental results show a satisfactory performance.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.371-374
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• 2011

Recently, retrieval of various video data has become an important issue as more and more multimedia content services are being provided. To effectively deal with video data, a semantic-based retrieval scheme that allows for processing diverse user queries and saving them on the database is required. In this regard, this paper proposes a semantic-based video retrieval system that allows the user to search diverse meanings of video data for electrical safety-related educational purposes by means of automatic annotation processing. If the user inputs a keyword to search video data for electrical safety-related educational purposes, the mobile agent of the proposed system extracts the features of the video data that are afterwards learned in a continuous manner, and detailed information on electrical safety education is saved on the database. The proposed system is designed to enhance video data retrieval efficiency for electrical safety-related educational purposes.

• 한국디지털정책학회:학술대회논문집
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• 2007.06a
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• pp.79-87
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• 2007

This paper aims to offer a solution based on semantic document classification to improve e-Government utilization and efficiency for people using their own information retrieval system and linguistic expression Generally, semantic document classification method is an approach that classifies documents based on the diverse relationships between keywords in a document without fully describing hierarchial concepts between keywords. Our approach considers the deep meanings within the context of the document and radically enhances the information retrieval performance. Concept Weight Document Classification(CoWDC) method, which goes beyond using exist ing keyword and simple thesaurus/ontology methods by fully considering the concept hierarchy of various concepts is proposed, experimented, and evaluated. With the recognition that in order to verify the superiority of the semantic retrieval technology through test results of the CoWDC and efficiently integrate it into the e-Government, creation of a thesaurus, management of the operating system, expansion of the knowledge base and improvements in search service and accuracy at the national level were needed.