Defining Views with Formal Concept Analysis for Understanding SPARQL Query Results

This new framework, namely Lattice Based View Access (LBVA), allows the classification of SPARQL query results into a concept lattice, referred to as views, for data analysis,

Using this gold standard, our experiments show that although features based on static characteristics of the query and statistics of changes in the data for individual predicates

1.1 Formal Concept Analysis for Interactive Query Refinement Formal Concept Analysis (FCA) has been used in corpus-based information retrieval for the construction and

This new framework, namely Lattice Based View Access (LBVA), allows the classification of SPARQL query results into a concept lattice, referred to as views, for data analysis,

This framework, called Lattice-Based View Access (LBVA), allows the classification of SPARQL query results into a concept lattice, referred to as a view, for data analysis,

This new framework, namely Lattice Based View Access (LBVA), allows the classification of SPARQL query results into a concept lattice, referred to as views, for data analysis,

This analysis shown in Figure 6 shows that participants found data source and triple pattern(s) related information helpful for understanding the query result derivation, but have

We believe that using content analysis ranking in combination with link analysis ranking which is powered by our data model and weighting mechanism, can improve accuracy of