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The optimization framework is based on the graph-cut method (Boykov and Marie-Pierre, 2001), which is briefly summarized.
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Their framework is based on atomic changes, including the addition or removal of RDF graphs statements.
The framework is based on three tiers.
This framework was based on earlier studies [10], [11].
The model is based on graph-based SSL [ 19, 20].
This data representation model is based on graph theory.
The method is based on the well known Cut Trees and centrality concepts on graphs.
This design is based on the fact that vertex-cut graph is more efficiently balanced than edge-cut graph [3, 13].
Vertex classification is based on the weight of the graph.
Firstly, our approach proposed in the paper is based on the primal framework of IsoRank algorithm which aimed at deterministic graph alignment.
This approach is based on the intuition of representing data points as a graph, finding cut point models of numeric attributes based on graph clustering, and transforming numeric to nominal data.
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