Abstract-As the number of Web 2.0 sites offering tagging facilities for the users' voluntary content annotation increases, so do the efforts to analyze social phenomena resulting from generated tagging and folksonomies. Most of these efforts provide different views for the understanding of various web activities.Results from various experimental research should be utilized to improve existing approaches underlying tagging data and contribute further to weaving the Web. However, in practice, there are not enough solutions taking advantage of these results. Even though we can mine social relations via tagging data, it proves no worth for users if this data cannot be reused.In this paper we propose a solution for tag data representation which allows data reuse across different tagging systems. To achieve this goal, we analyze current social tagging practices, existing folksonomy usage as well as Semantic Web approaches to data annotation and tagging. We survey and compare existing tag ontologies in an attempt to investigate mapping possibilities between different conceptual models. Finally, we present our method for federation among existing ontologies in order to generate re-usable, semantically-linked data that will underly tagging data.
Abstract.A multi-agent system is a network individual agent that work together to achieve a goal through communication and collaboration among each other. Standardized infrastructure for information or knowledge sharing is required to make autonomous agents interdependent on each other for effective collaboration in a multi-agent system. In order to enhance productivity of knowledge workers knowledge management tools should support collaborative environments among desktop, web, and even mobile devices. The Semantic Web is the place where software agents perform various intelligent tasks using standard knowledge representational schemes that are named "ontologies." This paper presents a conceptual framework of the social knowledge activities and knowledge processes with regard to the social software agents. Our prototype, called WANT, is a wiki-based semantic tagging system for collaborative and communicative knowledge creation and maintenance by a human or software agent. It can be supported in both desktop and mobile environments.
Purpose-The purpose of this research is to investigate some general features of folksonomies and user-generated content with copyright issues, and to present semantic representation for folksonomies using a tag ontology that can be used to represent tagging data at a semantic level using Semantic Web technologies. Design/methodology/approach-An exploratory study is described that features current social tagging methods and copyright metadata. In particular, a tag ontology is extended for representing copyright metadata across different platforms. Findings-The main finding is that Social Semantic Cloud of Tags can improve the expressive knowledge representation of folksonomies and that this ontology can aid in describing copyright metadata using some extended properties. Originality/value-The paper gives a valuable insight into representing folksonomies with Semantic Web technologies that enable the representation, exchange, and reuse of tagging data, and provides a way to reduce the risk of copyright infringements in the process of tag sharing in folksonomies.
We present a novel approach to build the contextualized folksonomy and concept hieracrhies from tags of blogosphere based on Formal Concept Analysis. Our approach is based on the assumption that if a blog has the relationships with others, they would use the similar set of tags. We collect the sample data from blogosphere randomly and then build the concept hierarchies on the basis of the inclusion relations(tags) between the extensions(bloggers). We propose the formalization of the contextualized folksonomy in terms of Formal Concept Analysis and show how our approach can be used to create the contextualized folksonmy for blogosphere. We evaluate our approach by considering an already existing tags of blogosphere.
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