Scalability and performance implications of semantic net visualization techniques are open research challenges. This paper focuses on developing a visualization technique that mitigates these challenges. We present a novel approach that exploits the underlying concept of power-law degree distribution as many realistic semantic nets seems to possess a power law degree distribution and present a small world phenomenon. The core concept is to partition the node set of a graph into power and non-power nodes and to apply a modified force-directed method that emphasizes the power nodes which results in establishing local neighborhood clusters among power nodes. We also made refinements in conventional force-directed method by tuning the temperature cooling mechanism in order to resolve 'local-minima' problem. To avoid cluttered view, we applied semantic filtration on nodes, ensuring zero loss of semantics. Results show that our technique handles very large scale semantic nets with a substantial performance improvement while producing aesthetically pleasant layouts. A visualization tool, NavigOWL, is developed by using this technique which has been ported as a plug-in for Protege, a famous ontology editor.

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Smartphones allow users to communicate with their social network [1] mostly through verbal, or written communication [2, 3] throughout the day [4, 5] except during resting periods [6]. The volume of this communication may roughly reflect the level of emotional attachment with various social relations [7, 8]. More specifically, if f 1 , f 2 ,. .. , f n , is the reverse sorted fractions of communication volume with n contacts of a user; then a large fraction of communication takes place with only a handful of initial contacts in this sequence [9-12]. Note that contacts can also be referred to as alters, in the sociological

Visualization has been extensively used in almost all the fields, but unfortunately, there is very little work on the visualization of flight search. The literature discusses only two representations: textual representation and linear representation. In this study, the authors introduce a new form of visualization called circular representation and compare it with the existing visualization techniques. The authors found that each representation has its own merits and demerits. More specifically, they found that users were able to find required flight circular efficiently when using circular representation, while most errors were committed by the user when using textual representation, and users ranked circular representation low in terms of qualitative satisfaction.