• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.389-392
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• 2006

Web 2.0은 사용자가 온라인에서 정보를 구축하고 공유하게 하는 World Wide Web 상의 2세대 서비스이다. Web 2.0 페이지에서는 사용자가 키워드인 태그를 이용하여 웹페이지나 인터넷상의 오브젝트를 분류하게 되는데 이를 Folksonomy 라 한다. Folksonomy 는 정보를 공동 작업으로 모으고 공유하는 사용자들에 의한 분류기법으로 Taxonomy 와는 다르며 장단점을 지니고 있다. 이 논문에서는 Folksonomy 의 단점중의 하나인 동의어 처리를 위하여 Wordnet 을 접목시킨 검색 기법을 제안한다.

• Journal of the Korean Society for Library and Information Science
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• v.42 no.4
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• pp.95-112
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• 2008

In contrast to traditional taxonomy, folksonomy is generated not only by experts but also by creators and consumers of the content. Folksonomy is the practice and method of collaboratively creating and managing tags to annotate and categorize content. It is also known as collaborative tagging or social indexing. Folksonomy is also used to link to create social network that connect people to people who share same interest. Folksonomy users can generally discover the contents by which the tag sets of another user who tends to interpret contents in a way that makes sense to them. Firstly, this study consider the significance and some critical issues about folksonomy. Secondly, analyze special features of Korean academic site's folksonomy, which is managed by academic information site. Accordingly consider the directions of development about folksonomy system.

• Journal of the Korean Society for Library and Information Science
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• v.42 no.4
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• pp.463-480
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• 2008

This study was to review the possible characteristics and patterns that occur when comparing control language constructing guidelines, by analyzing the formal characteristics of folksonomy tags in university libraries. Based on subjected tags at university libraries for a period of 6 months the structure and form of folksonomy was examined. The object tags were analyzed based on the thesaurus development guidelines. The results for this research will provide baseline data for the use of folksonomy tag applications in digital libraries.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.185-207
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• 2011

In the current information environment, many approaches have been adopted to represent and organize information resources. Among these approaches, folksonomy using tags is now being used in knowledge representation and organization. Although it may be an efficient approach to overcome the limitations of previous approaches, there are several problems in assigning tags such as ambiguity, inconsistency, and polysemy that limit efficient information organization. This research proposes a conceptual framework for the control of semantics of tags through linking up with bibliographic records in order to maximize the efficiency and minimize the limitations of folksonomy tags.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.13-20
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• 2009

The most of navigation services these days, are designed in order to just provide a shortest path from current position to destination for a user. Several navigation services provides not only the path but some fragmentary information about its point, but, the data tends to be highly restricted because it's quality and quantity totally depends on service provider's providing policy. In this paper, we describe the folksonomy POI(Point of interest) recommender system using mashup in order to provide the information that is more useful to the user. The POI recommender system mashes-up the user's folksonomy data that stacked by user with using external folksonomy service(like Flickr) with others' in order to provide more useful information for the user. POI recommender system recommends others' tag data that is evaluated with the user folksonomy similarity. Using folksonomy mahup makes the services can provide more information that is applied the users' karma. By this, we show how to deal with the data's restrictions of quality and quantity.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.1
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• pp.137-150
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• 2009

This study has introduced folksonomy to general patterns of folksonomy tags for the university libraries that have practically implemented Library 2.0. From the results, we can see that average about 1.35 tag is used for one content. Typical pattern of the tags follow a power function that frequency of use decreases as No. of uses increases, 79.51% of tags are expressing topic of contents, and 84.61% of tags are tag of social motivation. The results of analysis on increase/decrease rate for tags divided into 4 quarters said that A university library has big differences from quarters while B university library has similar data between quarters. The users have used average 5.25 tags. Trends of the users can be divided into 3 groups according to tagging patterns of the users.

• 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 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.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.1-10
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• 2007

Recently, the web 2.0 services which appear by exponential extension of the Internet can be expressed with the changes in the quality of structural evolution and in the quantity of increasing users. The structural base is in user participational architecture, the web 2.0 services such as Blog, UCC, SNS(Social Networking Service), Mash-up, Long tail, etc. play a important role in organization of web, and grouping and searching of user participational data in web 2.0 is broadly used by folksonomy. Folksonomy is a new form that categorizes by tags, not classic taxonomy skill. it is made by user participation. Searching based on tag is now done by a simple text or a tag cloud method. But searching to consider and express the relations among each tags is imperfect yet. Thus, this paper provides the relational searching based on tags using the relational graph of tags. It should improve the trust of the searching and provide the convenience of the searching.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.59-74
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• 2011

As more users are willingly participating in the creation of web contents, flat folksonomy using simple tags has emerged as a powerful instrument to classify and share a huge amount of knowledge on the web. However, flat folksonomy has semantic problems, such as ambiguity and misunderstanding of tags. To alleviate such problems, many studies have built structured folksonomy with a hierarchical structure or relationships among tags. However, structured folksonomy also has some fundamental problems, such as limited tagging to pre-defined vocabulary for new tags and the timeconsuming manual effort required for selecting tags. To resolve these problems, we suggested a new method of attaching a categorized tag (CT), followed by its category, to web content. CTs are automatically integrated into collaboratively-built structured folksonomy (CSF) in real time, reflecting the tag-and-category relationships by majority users. Then, we developed a CT-based knowledge organization system (CTKOS), which builds the CSF to classify organizational knowledge and allows us to locate the appropriate knowledge.