• 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 Korea Society of Computer and Information
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• v.14 no.11
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• pp.1-12
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• 2009

Mobbing is going the rounds through a society rapidly and Military is not exception. Because mobbing of military is expressed not only psychology exclusion that is mobbing pattern of adult society but also sometimes psychologic and physical mobbing, is possible to join serious military discipline like a suicide and outrageous behavior. Specially military try to protect occurrence of victims that is public service through various rules and management plan but victims is going on happen. It means importance of grasp not only current mobbing victims but also potential mobbing victims better than preparation of various rules and management plans. Therefore this paper extracts seven factors and fifty attributes that are related to this matter mobbing. Next, by using Gunwoo's Social Network Service that is made for oneself and expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function(Dice's coefficient) to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and propose Mobbing Value(MV) Algorithm through this total summation. Finally through this algorithm which will contribute to efficient personnel management, we can grasp mobbing victims and tentative mobbing victims.