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- W4385845461 abstract "PageRank is the most famous algorithm used for ranking of the search results which has been developed and used by the most famous search engine Google. It is used to order the list of web pages which are specific to the query. This algorithm’s simplicity makes it generic and a very powerful tool that can be used in a broad range of various applications. PageRank was most importantly designed to use the structure of a graph to measure the importance of nodes in the graph. It is this intuition that drives it to find its application in another most widely used algorithm, K-Means clustering algorithm. K-Means algorithm uses the centroids to cluster the nodes present in the graphs. PageRank can be used to find these centroids, that is, to find the nodes that have high centrality measure to cluster the nodes. Our work uses the PageRank as the method for finding the node that has the highest centrality for a particular cluster and uses it as the centroid to find the clusters for new iteration in K-Means algorithm. It uses Voronoi cells to determine the clusters iteratively using the centroids formed by the PageRank algorithm. We use the NetworkX PageRank module to determine the K center nodes that take the NetworkX graph as the input. The NetworkX module Voronoi cells is used to find the Voronoi cells, that is, clusters of the graph, which takes the centroids and NetworkX graph as input. The datasets used in this project are social circles from Facebook, Wikipedia who-votes-on-whom network, email communication network from Enron, Gnutella peer-to-peer network from August 4, 2002, and from August 6, 2002. Our methodology implements clustering of graphs using K-Means and PageRank which greatly improved the performance over the standard K-Means clustering for graphs. Our methodology achieved a considerable speed up by implementing the algorithm in a parallel paradigm. With parallel implementation, the speed up achieved on the above datasets ranged from 1.33 to 4.87 ms." @default.
- W4385845461 created "2023-08-16" @default.
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- W4385845461 date "2023-01-01" @default.
- W4385845461 modified "2023-09-27" @default.
- W4385845461 title "Parallel Implementation of PageRank Based K-Means Clustering on a Multithreaded Architecture" @default.
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- W4385845461 doi "https://doi.org/10.1007/978-981-99-2058-7_23" @default.
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