Survey of Graph Clustering Algorithms Using Amazon Reviews
نویسندگان
چکیده
We built a graph clustering system to analyze the different resulting clustering from Amazon’s product reviews from the dataset on SNAP. There are over 53MB of reviews, but we started from the graph constructed from the Jewelry set containing 60,000 nodes. Our focus for this graph clustering was the clustering product to ascertain whether the clusters were characterized by individual traits. We evaluated using SNAP’s ClausetNewman-Moore, Spectral Clustering, and Normalized Min-cut Clustering based on betweenness centrality. Our initial results shed light on some promising developments that support our initial hypothesis that clustered products and reviewers have similar attributes.
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