Understanding semantic web entity: Concept space based summarization method

To achieve fast and accurate understanding of semantic web entities, a concept space based summarization method is proposed. To organize the information, the resource description framework (RDF) data about an entity are partitioned into different concept spaces. In each concept space, the data are clustered by predicates. On the confidence of information, the authoritative dimension of RDF data is proposed. The value of this dimension is set according to the sources of the data. To address the scalability problem, an RDF data summarization method is proposed. The importance of data is asserted by its centrality in the graph structure, user preferences and the popularity of documents containing it. The results of experiments show that the proposed method is efficient in supporting the understanding of semantic web entities. Generally, the method is 4% to 17% faster than the state of art RDF browser. When the user is familiar with the RDF data model, the improvement can be 20%.