Prediction of Binary Labels for Edges in Signed Networks: A Random-Walk Based Approach
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Cites background from "Prediction of Binary Labels for Edg..."
...Some studies work on classifying edges as friends and enemies [7, 8, 9, 27, 28]....
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References
23,600 citations
"Prediction of Binary Labels for Edg..." refers background or methods in this paper
...Most of the data in the real-world are unstructured/semistructured and can be represented as graphs/networks in their natural setting [1]....
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...However, their approach requires measuring the similarity between nodes using Jaccard measure [1] which takes only the neighborhood information of nodes in the network which results in a low accuracy of edge labeling....
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4,205 citations
"Prediction of Binary Labels for Edg..." refers background in this paper
...A lot of work has been done for node labeling in networks [5], [6], [7]....
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2,937 citations
"Prediction of Binary Labels for Edg..." refers background in this paper
...Among various mining tasks, node classification or labeling is an important mining task in the network as it has numerous real-world applications [3], [4]....
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2,036 citations
"Prediction of Binary Labels for Edg..." refers background or methods in this paper
...Then for each network, we compute the similarity between nodes using SimRank which is a random-walk based structural similarity measure [15]....
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...The above equation iteratively computes the structural similarity between nodes [15]....
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...2) Compute random-walk based structural similarity between nodes using SimRank....
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...For that, we utilized SimRank which is a random-walk based measure to compute the similarity score between all pair of nodes [15]....
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...For computing the similarity between all pairs of the node, we use the following matrix form of the SimRank: ( ){ }1max ,K kTC A IS SA −= ⋅ ⋅ ⋅ (2) The above equation iteratively computes the structural similarity between nodes [15]....
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1,253 citations