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Personalised, serendipitous and diverse linked data resource recommendations

Abstract:

Due to the huge and diverse amount of information, the actual access to a piece of information in the Linked Open Data (LOD) cloud still demands significant amount of effort. To overcome this problem, number of Linked Data based recommender systems have been developed. However, they have been primarily developed for a particular domain, they require human intervention in the dataset pre-processing step, and they can be hardly adopted to new datasets. In this paper, we present our method for personalised access to Linked Data, in particular focusing on its applicability and its salient features.