Abstract
Web graph is a tool to visualize web information as network. It unfurls inherent connectivity of the web for end users from a different viewpoint. The enlarged size of the web causes the information overload problem and forces the wide use of compression techniques such as filtering and clustering on graphs during presentation of web information. In addition, the Internet users, their intentions and activities on the web differ. User interest-based web graph, which is modulated by user interests during construction, is used to accommodate differences over end users and/or their needs. However, user interest-based web graph features an unorthodox way to present connectivities among nodes by utilizing edge labels. This complicates further operations such as clustering and focused visualization on web graphs. This paper introduces a novel approach to cluster user interest-based web graphs by adopting the divide and conquer strategy. It is demonstrated that, this approach can effectively cluster the user interest-based web graph.
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Saleheen, S., Lai, W. (2014). An Interest-Based Clustering Method for Web Information Visualization. In: Luo, X., Yu, J.X., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2014. Lecture Notes in Computer Science(), vol 8933. Springer, Cham. https://doi.org/10.1007/978-3-319-14717-8_33
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DOI: https://doi.org/10.1007/978-3-319-14717-8_33
Publisher Name: Springer, Cham
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