Semi-automatic knowledge extraction to enrich open linked data

摘要: In this chapter we present the analysis of Wikipedia collection by means ELiDa framework with aim enriching linked data. is based on association rule mining, an exploratory technique to discover relevant correlations hidden in analyzed To compactly store large volume extracted knowledge and efficiently retrieve it for further analysis, a persistent structure has been exploited. The domain expert charge selecting setting filtering parameters, assessing quality knowledge, semantic expressiveness which cannot be automatically inferred. We consider, as representative document collections, seven datasets from collection. Each dataset two point views (i.e., transactions documents, sentences) highlight at different levels abstraction.