Efficient algorithm to compute Markov transitional probabilities for a desired PageRank
Abstract We propose an efficient algorithm to learn the transition probabilities of a Markov chain in a way that its weighted PageRank scores meet some predefined target values. Our algorithm does not require any additional information about the nodes and the edges in the form of features, i.e., it...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2020-07-01
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| Series: | EPJ Data Science |
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| Online Access: | http://link.springer.com/article/10.1140/epjds/s13688-020-00240-z |