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In a social tagging system, resources (such as photos, video and web pages) are associated with tags. These tags allow the resources to be effectively searched through tag-based keyword matching using traditional IR techniques. We note that in many such systems, tags of a resource are often assigned by a diverse
their personal file system by leveraging semantic relationships available on the Web. More specifically, JabberWocky is using keyword/resource associations of social bookmarking web sites as a basis for recommending keywords for files. We chose social bookmarking web sites because of their popularity and because the
Social tagging is a relatively new type of social software that stores user-generated textual keywords to describe a resource or aspects of that resource. In this paper we explore the mechanisms that social tagging can trigger to change the behavior of knowledge workers. We argue that social tagging has the potential
Social navigation and social tagging technologies enable user communities to assemble the collective wisdom, and use it to help community members in finding the right information. However, it takes a significantly-sized community to make a social system truly useful. The question addressed in this paper is whether collaborative information finding is feasible in the context of smaller communities...
Social tagging is the process by which many users add metadata in the form of keywords, to annotate and categorize items (songs, pictures, Web links, products, etc.). Social tagging systems (STSs) can provide three different types of recommendations: They can recommend 1) tags to users, based on what tags other users
Social bookmarking and other Web sites allow users submitting their resources and labeling them with arbitrary keywords, called tags, to create folksonomies. These sites usually provide their users tag recommendations in order to help them to find relevant information and resources. However, only very basic techniques
Folksonomy systems enable users to participate in the Web content creation process by annotating (tagging) resources with freely chosen keywords. Still, it is an open issue how to exploit this user-created content, and how to process and use these emergent semantics effectively. We investigate how the context of Web
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