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Linked Data is becoming one of the most important sources of information of the Web. Many projects (such as Linking Open Data –LoD- (Bizer et al. 2001) ) start to provide a huge amount of open data by following the key principles (Bizer et al. 2009) for publishing Linked Data. At the same time, making use of Linked Data for improving information retrieval is becoming an important field of research, especially with the widespread use of semantic search engines. In this paper we propose an approach based on Linked Data for improving user satisfaction during his interactions with an information retrieval system. We want to provide the users with more intelligent search results snippets, and to offer them a clustering of the results. In order to achieve this goal, we focus on the application of a graph ranking algorithm after having transformed the RDF (Lassila and Swick 1999) graphs into a bipartite graph (Biggs, Lloyd, and Wilson 1999) representation.

A Generic Approach Based on Linked Data to Enhance Web Information Retrieval and Increase User Satisfaction