Recommending Tripleset Interlinking through a Social Network Approach
Tripleset interlinking is one of the main principles of linked data. However, the discovery of existing triplesets relevant to be linked with a new tripleset is a non-trivial task in the publishing process. Without prior knowledge about the entire Web of data, a data publisher must perform an exploratory search, which demands substantial effort and may become impracticable, with the growth and dissemination of linked data. Aiming at alleviating this problem, this paper proposes a recommendation approach for this scenario, using a social network perspective.