• 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 Korea Information Processing Society Conference
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• 2013.11a
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• pp.1394-1396
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• 2013

플리커와 같은 대용량 영상저장 및 공유 사이트가 인기를 끌면서 이미지 정보의 양은 점점 늘어나고 있고 사용자들은 정확한 이미지 정보 검색을 요구하고 있다. 태그기반의 이미지 검색에서 정확도를 높이기 위하여 태그들의 의미적 연관성을 이용하는 등 다양한 연구가 진행되고 있다. 본 논문에서는 특징점 추출에 기반하여 이미지를 분류하는데 뛰어난 성능을 가진 SIFT알고리즘을 사용하여 플리커 이미지를 분류하는 방법을 제안한다. 위키피디아 의미 연관성을 이용해 태그 정보로 1차 분류된 데이터베이스에 SIFT알고리즘을 사용해본 결과 기존의 SURF를 사용한 연구보다 높은 정확성을 보이는 것을 확인하였다. 따라서 이 방법을 통하여 다양한 이미지를 더욱 정확하게 분류할 수 있을 것으로 기대한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.962-963
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• 2013

트위터 해시태그(#, HashTag)는 트윗(Tweets)에서 특정 키워드나 내용을 주제별로 분류하고 검색을 보다 효율적으로 사용하기 위한 사용자 정의 태그이다. 사용자가 정의하기에 따라 다양한 형태로 작성되기 때문에 오히려 검색의 효율성이 떨어질 수 있으며, 사용자는 자신이 작성한 트윗에 어떤 해시태그를 추가해야 하는지에 대한 궁금증이 생기는 경우가 발생한다. 본 논문에서는 이러한 문제를 해결하기 위해 사용자가 작성한 트윗에 적합한 해시태그를 추천하는 기법을 제안한다. 수집한 트윗과 해시태그의 키워드를 추출하고 트윗의 유사도를 계산하기 위해 TF-IDF와 Cosine Similarity를 적용하여 유사한 트윗을 갖는 해시태그를 추천한다. 본 논문에서 제안된 기법을 검증하기 위한 실험으로 추천의 정확성을 평가했다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.269-272
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• 2011

추천은 다양한 컨텐츠 중에서 사용자가 원하는 것을 선택할 수 있도록 돕는 것이다. 이러한 추천은 광고주가 자신의 광고에 적절한 컨텐츠를 찾을 때에도 활용될 수 있다. 본 논문에서는 광고를 표현하는 태그와 영화를 나타내는 주제어들을 매칭하여 광고에 적합한 영화를 추천하는 문제를 다룬다. 이 문제의 경우, 광고를 표현하는 태그의 개수가 적고, 영화의 주제어와 성격이 다른 경우가 많아 단순 매칭을 활용한 추천 기법으로는 결과를 얻을 수 없는 경우도 존재한다. 우리는 이러한 문제를 완화하기 위해 키워드 확장을 통한 추천 기법을 제안한다. 구체적으로 각 영화 컨텐츠가 가진 주제어를 위키피디아를 통해 검색하고 이를 통해 주제어를 확장한다. 광고의 태그 또한 위키피디아 검색을 통해 확장한다. 이렇게 확장된 영화 주제어와 광고 태그를 연관성 규칙에 기반하여 매칭한다. 실험 결과 단순 매칭보다 제안한 확장을 통한 매칭이 37.5%의 성능 향상을 보였다.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.181-195
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• 2010

The participation and share between personal users are the driving force of Web 2.0, and easily found in blog, social network, collective intelligence, social bookmarking and tagging. Among those applications, the social bookmarking lets Internet users to store bookmarks online and share them, and provides various services based on shared bookmarks which people think important.Delicious.com is the representative site of social bookmarking services, and provides a bookmark search service by using tags which users attach to the bookmarks. Our paper suggests a method re-ranking the ranks from Delicious.com based on user tags in order to provide personalized bookmark recommendations. Moreover, a method to consider bookmarks which have tags not directly related to the user query keywords is suggested by using tag network based on Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare the ranks by Delicious.com with new ranks of our system.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.75-94
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• 2010

This study designed a pilot system in which queries can be expanded through a tag ontology where equivalent, synonymous, or related tags are bound together, in order to improve the retrieval effectiveness of videos. We evaluated the proposed pilot system by comparing it to a tag-based system without tag control, in terms of recall and precision rates. Our study results showed that the mean recall rate in the structured folksonomy-based system was statistically higher than that in the tag-based system. On the other hand, the mean precision rate in the structured folksonomy-based system was not statistically higher than that in the tag-based system. The result of this study can be utilized as a guide on how to effectively use tags as social metadata of digital video libraries.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.50-54
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• 2007

정보기술은 통신 및 멀티미디어 기술의 발전에 힘입어 빠르게 발전되고 있으며, 이에 따른 데이타베이스의 기술이 공간데이타, XML, 비디오, 음성과 같은 다양한 멀티미디어 데이터 분야에 적용되고 있다. 비디오 데이타는 순차적인 특성을 가지며, 시간과 공간정보가 결합된 3차원 데이타로서 처리시간이 높은 작업이기 때문에 검색이나 브라우징이 대단히 비효율적이다. 본 논문에서는 비주얼리듬을 이용하여 비디오 데이타에서 대표 프레임(Key Frame)을 추출한 다음 XML을 이용한 태그 및 키워드 정보를 대표 프레임에 삽입하여 검색이나 브라우징을 할 수 있는 동영상 내용편집 도구(Authoring Tool for Video Contents)를 제안한다. 비주얼리듬은 3차원의 시공간적인 정보를 2차원으로 매핑한 정보로 IDCT(inverse Discrete Cosine Transform)과정 없이 픽셀 정보를 얻을 수 있어 처리속도가 빠르며 컷, 와이프, 디졸브 등의 편집효과를 효과적으로 구분할 수 있다. 그리고 XML 데이타에는 태그 및 정보와 함께 대표 프레임의 정보까지 저장되므로 유사 화면 검색이나 내용 기반 검색을 제공할 수 있다.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.1
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• pp.117-135
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• 2010

We designed a structured folksonomy system in which queries can be expanded through tag control; equivalent, synonym or related tags are bound together, in order to improve the retrieval efficiency (recall and precision) of image data. Then, we evaluated the proposed system by comparing it to a tag-based system without tag control in terms of recall, precision, and user satisfaction. Furthermore, we also investigated which query expansion method is the most efficient in terms of retrieval performance. The experimental results showed that the recall, precision, and user satisfaction rates of the proposed system are statistically higher than the rates of the tag-based system, respectively. On the other hand, there are significant differences among the precision rates of query expansion methods but there are no significant differences among their recall rates. The proposed system can be utilized as a guide on how to effectively index and retrieve the digital content of digital library systems in the Library 2.0 era.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.557-560
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• 2005

XML 문서의 논리적인 구조와 의미적 태그의 사용은 구조와 내용에 기반 한 검색을 가능하게 하는 반면, 동일한 정보라 하더라도 구조와 형식이 매우 다양하게 표현되므로 정보검색에 어려움을 초래한다. 효율적인 XML 정보검색을 위해, 본 논문은 온톨로지를 기반으로 검색에 적합한 문서만을 선별하는 문서여과 방법, 대상문서에 적합한 최소한의 질의생성을 위한 온톨로지 정합 방법 그리고 문서에 내재된 의미적 정보의 검색을 위한 정합된 온톨로지 기반의 질의확장 방법을 각각 제안하였다. 제안한 방법의 효과 및 효율은 예제 XML 및 DTD 문서를 대상으로 실험되었다.