Visual analysis framework for understanding missing links in bipartite networks
地域：
Tokyo
摘要
Example implementations described herein involve an interface for calculating and displaying missing links for data represented as a bipartite network, along with novel methods for improving link prediction algorithms in the related art. Through example implementations described herein, the accuracy of link prediction algorithms can be improved upon, thereby providing the user with a more accurate understanding of the data in the bipartite network.
說(shuō)明書
At 400, the flow detects bicliques within a bipartite network G=X, Y, E
and incorporates them into a list L={Ci=
Xi, Yi, Ei
}, with X and Y each being the set of nodes within the respective network of the bipartite network, and E representing the links that exist in the bipartite network. Bicliques can be detected by any method according to the desired implementation.
At 401, the flow initializes weights for all missing links e∈U?E, U={?x, y
; x∈X, y∈Y}, wherein U is the set of all possible links that could exist in the bipartite network. In an example implementation, the flow sets we←0 or other base value in accordance with the desired implementation.
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