• 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 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.

• 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.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.363-372
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• 2013

When retrieving music with folksonomy tags, internal use of numeric tags (AV tags: tags consisting of Arousal and Valence values ) instead of word tags can partially solve the problem posed by synonyms. However, the two predecessor tasks should be done correctly; the first task is to map word tags to their numeric tags; the second is to get numeric tags of the music pieces to be retrieved. The first task is verified through our prior study and thus, in this paper, its significance is seen for the second task. To this end, we propose the music mapping table defining the relation between AV values and music and ANOVA tests are performed for analysis. The result shows that the arousal values and valence values of music have different distributions for 12 mood tags with or without synonymy and that their type I error values are P<0.001. Consequently, it is checked that the distribution of AV values is different according to music mood.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1877-1893
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• 2009

Folksonomy is a user-generated taxonomy to organize information by which a user assigns tags to resources published on the web. Triadic datas that indicate relations of between users, tags, and resources, are created by collaborative tagging from many users in folksonomy-based system. Such the folksonomy data has been utilized in the field of the semantic web and web2.0 as metadata about web resources. In this paper, we propose FCA-based folksonomy data mining approach in order to extract the useful information from folksonomy data with various points of view. And we developed tool for supporting our approach. In order to verify the usefulness of our proposed approach and FMT, we have done some experiments for data of del.icio.us, which is a popular folksonomy-based bookmarking system. And we report about result of our experiments.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.203-230
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• 2010

This study analyzed the development and growth of folksonomy by examining tags associated with 40 bestsellers on LibraryThing.com in 6-month intervals. It was found that tag values do not decrease but grow in terms of quantity and quality. Accordingly, we examined the major significances of the tags and their potential utilization as an expression of subjects. Our findings were as follows. First, the motivations for tagging can be categorized into personal information for search purposes, self-fulfillment such as sense of achievement, display of emotion and sharing of one's experience with others, or an altruistic objective that emphasizes sociality with a desire that one's actions might provide social benefits. According to our analysis, 74.12% of tags had a social motivation. Second, the total number of tags and the frequency of usage increased with time. Third, the categories that showed a high increase in tag usage were dates of publication and reading, key words, main characters, and book reviews. Tags related to subjects had the highest ratio. Fourth, among Library of Congress Subject Headings (LCSH), multiple genres, key words and main characters were assigned to books, and specific key words and other properties were added as time progressed. There was also a slight increase in the number of tags consistent with LCSH. Fifth, we found that key tags could serve as a compilation of terms that reflects the knowledge base of the corresponding era. Thus, folksonomy should be continuously monitored for its quantitative and qualitative development of the tags to make improvements on its formative disadvantages, and identify internal semantic significance, be actively utilized in conjunction with taxonomy as a flexible compilation of terms that incorporate the history of a specific era.

• Journal of Korean Library and Information Science Society
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• v.40 no.4
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• pp.381-400
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• 2009

This study intends to make a comprehensive inquiry into the meaning and limitations of Folksonomy, and to explore how to make full use of Folksonomy in library cataloging. To this end, this study examined as follows : (1) how the philosophical meaning of Folksonomy is different from traditional principles of library cataloging, (2) what the viewpoint of LIS scholars toward Folksonomy are, and how North American libraries have customized Folksonomy for their catalogs. In addition, (3) usefulness of Folksonomy in library catalogs is thoroughly discussed. Based on these, (4) the final discussion includes strategies for Korean LIS scholars and library practitioners to consider when applying Folksonomy to Korea library contexts.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.82-88
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• 2017

Recently recommendation methods need personalization and diversity as well as accuracy whereas the traditional researches have been mainly focused on the accuracy of recommendation in terms of quality. The diversity of recommendation is also important to people in terms of quantity in addition to quality since people's desire for content consumption have been stronger rapidly than past. In this paper, we pay attention to similarity of data gathered simultaneously among different types of contents. With this motivation, we propose an enhanced recommendation method using correlation analysis with considering data similarity between two types of contents which are movie and music. Specifically, we regard folksonomy tags for music as correlated data of genres for movie even though they are different attributes depend on their contents. That is, we make result of new recommendation movie items through mapping music folksonomy tags to movie genres in addition to the recommendation items from the typical collaborative filtering. We evaluate effectiveness of our method by experiments with real data set. As the result of experimentation, we found that the diversity of recommendation could be extended by considering data similarity between music contents and movie contents.