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ISBN: 978-972-8939-25-0 © 2010 IADISideas of (Adamic and Adar 2005) to evaluate the actual efficiency of the system to retrieve related documentsusing tag cloud driven navigation. In order to support efficient search, the searcher uses a hierarchicalconcept model as background knowledge (in our case a tag – taxonomy = tagonomy) to find related contentwithin a tag cloud network (see Algorithm 1).Searcher(, ,)T ← GetTagonomy(∞, G)currentNode ← STARTwhile currentNode != TARGET doneighbors ← get all adjacent nodes ∈ G from currentNode// finds closest node according to dist = min, where dist(A,B) = h(A)+h(B)-2h(A,B)-1currentNode ← findClosestNode (neighbors, T)end while// generates a tag – Taxonomy using cosine similarityGetTagonomy(, )tagonomy ← nulltags ← GetMostImportantTags(G) //returns a tag list sorted in desc. order using tag frequencyroot ← tags[0]visitedList ← rootfor each parent ∈ tags and not contained in visitedList dochildTags ← getSimTags() // returns a list of similar tags using cosine similarity measuresvisitedList ← childTagsfor each child ∈ childTags