• Journal of Korean Library and Information Science Society
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• v.50 no.4
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• pp.381-403
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• 2019

Information on newspaper articles were categorized into different topics, and each categories within different topics were developed into a faceted taxonomies model which was combined with fundamental facets. After suggesting the plan to construct such a model, the research of actual faceted taxonomies were conducted. Faceted taxonomies divide information on news articles into different topics(such as politics, economies and others) and combine fundamental facets with categories(for example, politics can be sub-classified into general politics, administration, legal system, and others) and sub-categories. Each sub-categories can be further subdivided. In taxanomies, categories can have hierarchical relationships. Categories-Facets, for example, can be utilized to combine "arts" with "people", "action", "event", "time", "place" and others. And Sub-category of the classification of "arts" such as "art," "music," "dance" form hierarchical relationships with "arts" and, in turn, can be used for browsing and further inferences. Furthermore, combining category and facets results in hierarchical structure in order of fundamental facets. As for the pilot vocabulary construction, faceted taxonomies of 145 words from news paper articles on the topic of "arts" were constructed using all construction elements covered in this study.

• Journal of Korean Library and Information Science Society
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• v.49 no.3
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• pp.263-282
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• 2018

This study analyzed nineteen best-practices (161 sub-programs) regarding school library media program. The authors conducted content analysis based on The Library Media Specialist's Taxonomy and the CIPP Model. In the analysis of taxonomy showing the degree of involvement of librarian teachers, Level Seven indicating a concerted effort to promote school library program was the most important (37.6%). Among the ten levels of taxonomy, the highest level (levels 6 to 10, high involvement of librarians) accounted for 65.9%. According to the analysis of the CIPP Model, (Context) most of the excellent programs were aimed at reading education (41.5%) and library use education (11.3%), and more than half (53.8%) cases were initiated by learners' needs. (Input) excellence programs employed various teaching materials and were operated at fixed time. (Process) the programs were run in a variety of ways, mainly with reading instruction (30.4%) and cultural activities (17.3%). (Product) As a fruit of programs, students and parents' satisfaction, students' achievement, self-confidence, and self-improvement were reported.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.406-409
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• 2008

We consider the problem of exploiting a taxonomy of propositionalized attributes in order to learn compact and robust classifiers. We introduce Propositionalized Attribute Taxonomy guided Naive Bayes Learner (PAT-NBL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact and accurate classifiers. PAT-NBL uses top-down and bottom-up search to find a locally optimal cut that corresponds to the instance space from propositionalized attribute taxonomy and data. Our experimental results on University of California-Irvine (UCI) repository data sets show that the proposed algorithm can generate a classifier that is sometimes comparably compact and accurate to those produced by standard Naive Bayes learners.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.414-423
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• 2009

Folksonomy, which is collaborative classification created by freely selected keywords, is one of the driving factors of the web 2.0. Folksonomy has advantage of being built at low cost while its weakness is lack of hierarchical or systematic structure in comparison with taxonomy. If we can build classifier that is able to classify web resources from collective intelligence in taxonomy, we can build taxonomy at low cost. In this paper, targeting folksonomy in Slashdot.org, we define a general model and show that collective intelligence, which can build classifier, really exists in folksonomy using a stability value. We suggest method that builds SVM classifier using stability that is result from this collective intelligence. The experiment shows that our proposed method managed to build taxonomy from folksonomy with high accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2357-2364
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• 2008

In this paper, we consider the problem of exploiting a taxonomy of propositionalized attributes in order to generate compact and robust classifiers. We introduce Propositionalized Attribute Taxonomy guided Naive Bayes Learner (PAT-NBL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact and accurate classifiers. PAT-NBL uses top-down and bottom-up search to find a locally optimal cut that corresponds to the instance space from propositionalized attribute taxonomy and data. Our experimental results on University of California-Irvine (UCI) repository data set, show that the proposed algorithm can generate a classifier that is sometimes comparably compact and accurate to those produced by standard Naive Bayes learners.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.4
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• pp.241-264
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• 2009

The study proposed an electronic journal retrieval model to be used to improve the retrieval efficiency of e-journals. To do this, firstly, we reviewed the literature on users' information behavior and on ERM (Electronic Resource Management) systems. Secondly, we conducted an e-mail survey of 96 participants (professors and graduate students) to find out about their information behavior on how to access, use and evaluate electronic resources as well as scientific information. Thirdly, we administered case studies on two ERMSs, Ex Libris' Verde and Innovative's Millennium. The proposed model will be operated within ERM systems and it enables to the supply of both system- and user-based services by combining taxonomy-based ERM systems with tag folksonomy. The model is unique in that it includes not only the automatic tagging functions that can be performed using log files but also the tag management functions including grouping similar or related tags.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.31-36
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• 2010

최근 대두되고 있는 웹2.0의 특징은 일반 사용자들이 능동적으로 정보를 생산해내고 공유하는데 있다. 웹 2.0의 참여형 아키텍쳐를 구성하는 핵심요소로 인식되고 있는 폭소노미(Folksonomy)는 과거 택소노미(Taxonomy)와 같이 전문가에 의하여 구축되는 분류 체계가 아닌 사용자들이 협동적으로 태그(Tag)들을 만들고 관리하는 소셜 태깅(Social Tagging)에 의한 분류 시스템이다. 최근 이러한 폭소노미를 활용하여 이미지를 공유하고 검색하고자 하는 다양한 시도들이 진행되고 있다. 그러나 Flickr와 같은 태그 기반 이미지 공유 시스템에서는 태그의 문법적, 의미적 모호성과 이미지에 대한 태그들의 중요성 또는 상관관계를 고려하지 않아 태그 기반 검색 시 정확성 및 신뢰성을 보장할 수 없다. 이러한 문제를 해결하기 위해 폭소노미에 기반한 이미지 공유 데이터베이스에서 적합한 태그들을 태그 전달(Tag Propagation)하거나 확률 및 출현빈도에 기반하여 태그 랭킹을 수행하기 위한 연구들이 활발히 진행되고 있지만 여전히 만족할만한 성능을 보이지 못하고 있다. 본 논문에서는 이미지 공유 데이터베이스에서 유사한 이미지들로부터 이미지에 보다 적합한 태그들을 부여하기 위해서, WordNet을 활용하여 태그들 간의 의미관계에 기반한 효율적인 태그 랭킹 기법을 제안한다. 또한, 신뢰성 있는 태그 기반 검색을 위하여 제안한 태그 랭킹 기법이 현재 이미지 공유 시스템의 랭킹 결과보다 정확성을 높일 수 있음을 실험 예제를 통하여 확인하였다.

• Journal of Korean Library and Information Science Society
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• v.50 no.1
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• pp.273-291
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• 2019

This study aims to extend fundamental categories from Clause 11, "facet analysis" in International Standards for thesaurus(ISO 25964-1) by analyzing fundamental categories of Clause 11 and concept and their scope in a thesaurus of Clause 5. For to do this, the fundamental categories were established by adjusting partially and adding mental entities explicitly referencing the highest concepts(YAMATO which is the upper ontology of Mizoguchi, and ISO 2788) and existing fundamental categories(PMEST, FRBR group 3 entities, 13 categories in CRG). Also, established fundamental categories were reorganized and structured based on concreteness/abstraction of PMEST in Ranganathan and independence/dependence of YAMATO in Mizoguchi. And the upper categories were divided into independent and dependent entities. Under these entities 28 criteria are included in the independent ones and 2 criteria in the dependent ones. In the further study, the result of this study can be expected to reuse and refer as controlled vocabulary in the field like classification, taxonomies and thesauri where expected to utilize fundamental categories and as the high-level concept when constructing an ontology for information retrieval.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.18 no.2
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• pp.141-159
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• 2007

The purpose of this study was to try to conceptualize the Folksonomy, so called collaborative taggng or bookmarking and suggest its application on the Web information services. This paper explores how folksonomies could be used in web information services to enable end users to manage personal information spaces, get helped existing controlled vocabularies, and create and share their interests in online communities. Traditional classification system and philosophical issues on Folksonomy were reviewed in this paper in the context of internet based information and its services. The benefits and shortcomings of folksonomies are discussed. Some of the customizable features in existing library catalogue systems are reviewed to suggest other applicable features for web information services.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.826-833
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• 2009

Currently, the rise of social tagging has changing taxonomy to folksonomy. Tag represents a new approach to organizing information. Nonhierarchical classification allows data to be freely gathered, allows easy access, and has the ability to move directly to other content topics. Tag is expected to play a key role in clustering various types of contents, it is expand to network in the common interests among users. First, this paper determine the relationships among user, tags and resources in social tagging system and examine the circumstances of what aspects to users when creating a tag related to features of websites. Therefore, this study uses tags from the social bookmarking service 'del.icio.us' to analyze the features of tag words when adding a new web page to a list. To do this, websites features classified into 7 items, it is known as tag classification related to resources. Experiments were conducted to test the proposed classify method in the area of music, photography and games. This paper attempts to investigate the perspective in which users apply a tag to a webpage and establish the capacity of expanding a social service that offers the opportunity to create a new business model.