The quality of the current tagging services can be greatly improved if the service is able to cluster tags by their meaning. Tag clouds clustered by higher level topics enable the users to explore their tag space, which is especially needed when tag clouds become large. We demonstrate TagCluster – a tool for automated tag clustering that harnesses knowledge from Wikipedia about semantic relatedness between tags and names of categories to achieve smart clustering. Our approach shows much better quality of clusters compared to the existing techniques that rely on tag co-occurrence analysis in the tagging service.
Increasingly Wikis are used to support existing corporate knowledge processes. Wikis are an appropriate software solution to support these processes because of their specific design principles. However, it is not yet proven whether Wikis are an adequate knowledge management tool. This paper presents a new approach to analyze existing networks in Wikis. Four perspectives on Wiki networks are introduced to investigate all dynamic processes and their interrelationships in a Wiki information space. The Social Network Analysis (SNA) is used to uncover existing structures and temporal changes. Additionally, a data set of a corporate Wiki is used to present an analysis which has been carried out. Results of analyzes work can be utilized to improve the existing knowledge processes in a company.