Given a directed social graph, we have to predict missing edges to recommend friends/connnections/followers in the graph.
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Updated
Jul 25, 2019 - Jupyter Notebook
Given a directed social graph, we have to predict missing edges to recommend friends/connnections/followers in the graph.
A graph mining problem where the task was to predict a link between the given nodes. Engineered different features like Jaccard Distance, Cosine-Similarity, Shortest Path, Page Rank, Adar Index, HITS score and Kartz Centrality. Finally built non-linear models to get the final F1 score as 0.92.
Given a directed social graph, have to predict missing links to recommend users.
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