Toward the Design of a Recommender System: Visual Clustering and Detecting Community Structure in a Web Usage Network

The identification of community structure is one of the fundamental questions in the analysis of large scale complex networks. In this work, we propose a novel approach to extracting communities within a large network of cyber learners and learning resources. The technique used is a heuristic which initially performs clustering using force-based visualization algorithms and then relies on network modularity to select good decompositions from those found visually. Through testing, we have determined appropriate parameters for optimal performance. Finally, we use the community detection method to design a visual recommender system to recommend learning resources to cyber learners within the same community.