Representation of Call-Duration and Social Graph as Multi-Layer Graphs
A Graph Mining Techniques
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Sometimes social networks frequently require multiple distinct types of connectivity information which can finally be derived as layers. This type of information retrieval can be represented as multi-layer graphs, where each layer contains a set of edges over the same underlying nodes of the base layer. The author proposes two algorithms namely MulCaDu and SoGraM. The first algorithm, MulCaDu represents a call-duration telephone graph as a multi-layer graph. So a total of four layers are generated namely base layer, sublayer-1 (low-call), sublayer-2 (medium-call), and sublayer-3 (high-call) re...
Sometimes social networks frequently require multiple distinct types of connectivity information which can finally be derived as layers. This type of information retrieval can be represented as multi-layer graphs, where each layer contains a set of edges over the same underlying nodes of the base layer. The author proposes two algorithms namely MulCaDu and SoGraM. The first algorithm, MulCaDu represents a call-duration telephone graph as a multi-layer graph. So a total of four layers are generated namely base layer, sublayer-1 (low-call), sublayer-2 (medium-call), and sublayer-3 (high-call) respectively. The second algorithm, SoGraM represents a social graph as a multi-layer graph. For this, the author has chosen three examples of social graph namely Author Graph, Email Graph, and Telephone Graph. So, the Algorithm, SoGraM has successfully represented the Author Graph, Email Graph, and Telephone Graph as multi-layer graphs with three layers, four layers, and five layers respectively.
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