• Journal of Digital Contents Society
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• v.8 no.3
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• pp.255-262
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• 2007

Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs, videos and other content. In this paper, we analyze the structure and basic knowledge of collaborative tagging systems as well as their dynamical aspects. We also present a retrieval system, TagPlus, using synonym tag that is derived from WordNet database. Specifically, TagPlus, a synonym tag based system has users retrieve images from Flickr system. The proposed system show the images tagged by not only the tag that users input but also the synonyms that are synonyms with the tag.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.193-201
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• 2009

The use of tagging to describes web documents in the form of keyword has experienced rising popularity among various web services. Tagging also plays an important role in collaborative bookmarking services which can be regarded as an online favorite bookmark service. Tags which are created by users make it easier to search other users' bookmarks as well as user's own bookmarks. In this paper we analyze usage patterns of collaborative tagging for exploring factors influencing the number of tags in web documents and users. We discovered that user's characteristics have more effect on the tags than the web documents' characteristics. Moreover, leading users contribute to make a variety of tag than following users. Our study implies that more knowledge can be created through the incentives for leading user in order to improve the service quality of tagging service.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.157-177
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• 2008

Even in a single day, an enormous amount of content including digital videos, posts, photographs, and wikis are generated on the web. It's getting more difficult to recommend to a user what he/she prefers among these contents because of the difficulty of automatically grasping of content's meanings. CF (Collaborative Filtering) is one of useful methods to recommend proper content to a user under these situations because the filtering process is only based on historical information about whether or not a target user has preferred an item before. Collaborative Tagging is the process that allows many users to annotate content with descriptive tags. Recommendation using tags can partially improve, such as the limitations of CF, the sparsity and cold-start problem. In this research, a CF method with user-created tags is proposed. Collaborative tagging is employed to grasp and filter users' preferences for items. Empirical demonstrations using real dataset from del.icio.us show that our algorithm obtains improved performance, compared with existing works.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.179-188
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• 2007

디지털 기기 가 보편 화 되 면서 많 은 디지털 컨텐츠가 생성되고 있다. 또한, 인터넷 서비스의 발전으로 이들 컨텐츠를 과거에 비해 손쉽게 웹 상에 개제할 수 있게 되 었다. 따라서, 많은 컨텐츠를 추 천해 주기 위해 추천 시스템에 관한 연구가 활발히 진행되고 있다. 이들 컨텐츠가 기존의 텍스트 기반에서 사진이나 동영상, 사운드 등 컴퓨터가 자동으로 내용을 파악하기 힘든 컨텐츠로 변화하면서, 내용의 파악이 필요 없 는 협력적 여 과(Collaborative Filtering)가 추천 시스템에서 유 용하게 이 용될 수 있다. 또한 web 2.0의 영향으로 컨텐츠를 분류하고 재검색을 용이하게 하기 위해 태깅(tagging)을 제공하는 서비스가 많아지고 있다. 본 논문에서는 내용 파 악이 힘든 컨텐츠의 효과적인 추천을 위해 협력적 여과(Collaborative Filtering)와 협력적 태깅(Collaborative Tagging)을 접목시킨 방법을 제안하고, 전통적인 협력적 여과 방법과 제안한 방법의 비교 실험을 통하여 협력적 여과 방법에서의 태 깅의 효과에 대 해 논한다.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.79-87
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• 2015

With recent emergence of Web 2.0 technology, many services are encouraging the user participation. Then, many approaches dealing with multimedia contents focused on the personalized information provisioning. The proposed approach analyzes the user requirements and previous methodology for personalized information provisioning. Furthermore, we propose the user participation based multimedia services with collaborative tagging.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.1068-1072
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• 2014

We propose a collaborative social tagging for eBook using external DSL approach. The goal of this paper is (1) to provide DSL by which authors can write HTML5 rich contents ebook and tag resources, (2) to make users enhance book by tagging resources easily, (3) to make readers read rich book easily regardless of their devices types, (4) to provide ebook resources of RESTful address style by which other system can identify self-descriptive resources of book. To achieve the goal, we provide Bukle DSL language by which author and users can author and enhance ebook with ease. As a domainspecific language Bukle provides a simple yet expressive language for authoring and tagging books that would otherwise be more difficult to express with a general purpose language. Further work includes visual DSL approach and tools by using that the unskilled users could tag book easily. In order that future work also includes text-to-visual DSL transform engine. UX research is also required to tag and to author book. To tackle the above questions we are looking at using visual notation focusing visual syntax.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.4
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• pp.327-351
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• 2009

This study analyzed the characteristics and functions of tags in academic libraries and commercial sites. Tags in tag clouds from 6 different sites were collected in terms of tag popularity and importance. The gathered tags were analyzed in terms of tagging purpose, the tagging function, and the physical characteristics of tags. The results can be used to apply the tagging service to academic digital libraries.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.4
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• pp.401-411
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• 2008

Folksonomy, which is created through the collaborative tagging from many users, is one of the driving factors of Web 2.0. Tags are said to be the web metadata describing a web document. If we are able to find the semantic subsumption relationships between tags created through the collaborative tagging, it can help users understand the metadata more intuitively. In this paper, targeting del.icio.us tag data, we propose a method named FolksoViz for deriving subsumption relationships between tags by using Wikipedia texts. For this purpose, we propose a statistical model for deriving subsumption relationships based on the frequency of each tag on the Wikipedia texts, and TSD(Tag Sense Disambiguation) method for mapping each tag to a corresponding Wikipedia text. The derived subsumption pairs are visualized effectively on the screen. The experiment shows that our proposed algorithm managed to find the correct subsumption pairs with high accuracy.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.143-149
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• 2010

In ubiquitous environment, information retrieval using collaborative filtering is a popular technique for reducing information overload. Collaborative filtering systems can produce personal recommendations by computing the similarity between your preference and the one of other people. We integrate the collaboration filtering method and context-aware information retrieval method. The proposed method enables to find some relevant information to specific user's contexts. It aims to makes more effective information retrieval to the users. The proposed method is conceptually comprised of two main tasks. The first task is to tag context tags by automatic tagging technique. The second task is to recommend items for each user's contexts integrating collaborative filtering and information retrieval. We describe a new integration method algorithm and then present a u-commerce application prototype.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.101-104
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• 2012

최근 소설 네트워크 서비스(Social Netwrok Services)를 활용한 소설 태깅 서비스에 대한 연구가 활발하게 진행 중이다. 특히 태그 기술을 이용한 협력적 태깅 시스템(collaborative tagging system)은 북마크, 문서, 사진, 동영상과 같은 웹 자원을 조직화하고 공유할 수 있는 수단으로 제공하고 있다. 그러나 광고 홍보 목적을 가진 스패머들은 콘텐츠와 관련 없는 태그를 달아 놓아 검색 키워드와 무관한 결과 값이 검색되어 웹 검색 서비스를 이용하는 사용자들에게 불편을 주고 있다. 따라서 본 연구에서는 콘텐츠와 태그의 연관성을 높이기 위해 태그에 일반 사용자가 유사도를 입력할 수 있는 추천 시스템을 적용하여 순위 조작 방지방법을 제안하였다.