Abstract
Connectivity and relatedness of Web resources are two concepts that define to what extent different parts are connected or related to one another. Measuring connectivity and relatedness between Web resources is a growing field of research, often the starting point of recommender systems. Although relatedness is liable to subjective interpretations, connectivity is not. Given the Semantic Web’s ability of linking Web resources, connectivity can be measured by exploiting the links between entities. Further, these connections can be exploited to uncover relationships between Web resources. This chapter describes the application and expansion of a relationship assessment methodology from social network theory to measure the connectivity between documents. The connectivity measures are used to identify connected and related Web resources. The approach is able to expose relations that traditional text-based approaches fail to identify. The proposed approaches are validated and assessed through an evaluation on a real-world dataset, where results show that the proposed techniques outperform state of the art approaches. Finally, a Web-based application called Cite4Me that uses the proposed approach is presented.
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Nunes, B.P., Fetahu, B., Kawase, R., Dietze, S., Casanova, M.A., Maynard, D. (2015). Interlinking Documents Based on Semantic Graphs with an Application. In: Tweedale, J., Jain, L., Watada, J., Howlett, R. (eds) Knowledge-Based Information Systems in Practice. Smart Innovation, Systems and Technologies, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-319-13545-8_9
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DOI: https://doi.org/10.1007/978-3-319-13545-8_9
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