• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1898-1904
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• 2009

Recently, real documents such as newspapers as well as blogs include newly coined words such as "Wikipedia". However, most previous information processing technologies cannot deal with these newly coined words because they construct their dictionaries based on materials acquired during system development. In this paper, we propose a model to automatically recognize Korean unknown words excluded from the previously constructed dictionary. The proposed model consists of an unknown noun recognition phase based on full text analysis, an unknown verb recognition phase based on web document frequency, and an unknown noun recognition phase based on web document frequency. The proposed model can recognize accurately the unknown words occurred once and again in a document by the full text analysis. Also, the proposed model can recognize broadly the unknown words occurred once in the document by using web documents. Besides, the proposed model fan recognize both a Korean unknown verb, which syllables can be changed from its base form by inflection, and a Korean unknown noun, which syllables are not changed in any eojeol. Experimental results shows that the proposed model improves precision 1.01% and recall 8.50% as compared with a previous model.

• 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 the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.75-81
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• 2016

My proposed Co-creation platform software analysis and design method in my paper, presents build technology of co-creation platform using Co-creation concepts refer to all process from products' idea level to products' design, manufacturing and marketing level. And this method can be possible to design and implement to be interlocked with company's cloud service and system through own SNS functions and OPEN API to build co-creation platform. Also owing to apply Wiki technology in the process of idea modification and completion level and provide cooperative work tools of story-board prototyping, it can be participate actively in the design process with customer and stakeholder together and realize functions to apply opinions. Therefore, Co-creation platform software analysis and design by objected-oriented analysis method is presented to show these design process effectively.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.353-362
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• 2016

By Wikipedia, data mining is the process of discovering patterns in a big data set involving methods at the intersection of association rule, decision tree, clustering, artificial intelligence, machine learning. and database systems. Association rule is a method for discovering interesting relations between items in large transactions by interestingness measures. Association rule interestingness measures play a major role within a knowledge discovery process in databases, and have been developed by many researchers. Among them, the Hellinger measure is a good association threshold considering the information content and the generality of a rule. But it has the drawback that it can not determine the direction of the association. In this paper we proposed a signed Hellinger measure to be able to interpret operationally, and we checked three conditions of association threshold. Furthermore, we investigated some aspects through a few examples. The results showed that the signed Hellinger measure was better than the Hellinger measure because the signed one was able to estimate the right direction of association.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.3
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• pp.181-201
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• 2012

This study aims to analyze and compare the structures of auxiliary tables regarding places - for example, Korea using several decimal classification systems such as DDC, UDC, KDC and NDC. For each auxiliary table, the codes were described in detail and the special characteristics were discussed. The common characteristics and the different aspects of different decimal classification systems were investigated as well as divisions of Korea in Korean Wikipedia and an administrative district classification system. This study suggests a new basic summary for the expansion of codes of Korea in auxiliary table in DDC with its principles and options and it will be useful for revising process of many decimal classification systems.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.95-99
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• 2010

Social media refers to the content, which are created by users, such as blogs, social networks, and wikis. Recently, question-answering (QA) communities, in which users share information by questions and answers, are regarded as a kind of social media. Thus, QA communities have become a huge source of information for the past decade. However, it is hard for users to search the exact question-answer that is exactly matched with their needs as the number of question-answers increases in QA communities. This paper proposes an approach for classifying a question into three categories (information, opinion, and suggestion) according to the purpose of the question for more accurate information retrieval. Specifically, our approach is based on modified Na$\ddot{i}$ve Bayes classifier which uses structural characteristics of QA documents to improve the classification accuracy. Through our experiments, we achieved about 71.2% in classification accuracy.

• Journal of the Korean Society for information Management
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• v.27 no.3
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• pp.35-51
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• 2010

Emerging Web 2.0 services such as Twitter, Blogs, and Wikis alongside the poorlystructured and immeasurable growth of information requires an enhanced information organization approach. Ontology has received much attention over the last 10 years as an emerging approach for enhancing information organization. However, there is little penetration into current systems. The purpose of this study is to propose ontology implementation and methodology. To achieve the goal of this study, limitations of traditional information organization approaches are addressed and emerging information organization approaches are presented. Two ontology data models, RDF/OW and Topic Maps, are compared and then ontology development processes and methodology with topic maps based medical information retrieval system are addressed. The comparison of two data models allows users to choose the right model for ontology development.

• Journal of the Korean Society for information Management
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• v.27 no.3
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• pp.241-264
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• 2010

This study aimed to construct the Library Map Information System(LMIS) based on the Wiki theory of Web 2.0. We built this system because there was no collective source of information about every library in the world. Also, this system was developed to provide a library location information service by mashing-up with the Google Map. Through this study, the metadata applied to the newly constructed system was developed by using the Delphi method. A total of 13 experts including librarians of schools, public, academic, special, and national libraries as well as LIS faculty members and researchers, were commissioned as Delphi experts. Through three rounds of a Delphi survey analysis, the addition, modification, and deletion of the initial metadata elements was accomplished, and then the library contact/location information, library information, collection information, and event information was proposed. The metadata for LMIS was organized into four sectors and then 49 elements, each assigned to a sector.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1491-1499
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• 2011

Now a days, to make good use of tags is a general tendency when users need to upload or search some multimedia data such as images and videos on the Web. In this paper, we introduce an approach to calculate semantic importance of tags and to make re-ranking with them on tagged Web image retrieval. Generally, most photo images stored on the Web have lots of tags added with user's subjective judgements not by the importance of them. So they become the cause of precision rate decrease with simple matching of tags to a given query. Therefore, if we can select semantically important tags and employ them on the image search, the retrieval result would be enhanced. In this paper, we propose a method to make image retrieval re-ranking with the key tags which share more semantic information with a query or other tags based on Wikipedia-based semantic relatedness. With the semantic relatedness calculated by using huge on-line encyclopedia, Wikipedia, we found the superiority of our method in precision and recall rate as experimental results.

• Journal of The Korean Association of Information Education
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• v.10 no.1
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• pp.13-22
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• 2006

Students should be able to find information and resources using the Internet. Also students need to have composite intellectual abilities to select information, convert to knowledge and communicate it to other people. However, most school and classroom homepages provide students with information but not contents that help them produce knowledge. This lowers the rate of connection to homepage. Thus, the purpose of this study is to develop and apply homepage, which helps students make knowledge from comprehended and interpreted information(Knowledge.Sharing Technique; KST). In this study we use 'WIKI KST' and 'Q&A KST' to share knowledge. WIKI KST is 'an encyclopedia that we make,' which means that students upload their prior knowledge or knowledge produced from comprehended and interpreted information and create new knowledge to be added to their own knowledge and others'. As a result, the abilities to comprehend and interpret acquired information are improved and the ability to change implicit knowledge to explicit knowledge is also improved. Students create new knowledge to share their knowledge and, as a result, the rate to connection to homepage gets higher.