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- W2605118527 abstract "A multimodal network encodes relationships between the same set of nodes in multiple settings, and network alignment is a powerful tool for transferring information and insight between a pair of networks. We propose a method for multimodal network alignment that computes a matrix which indicates the alignment, but produces the result as a low-rank factorization directly. We then propose new methods to compute approximate maximum weight matchings of low-rank matrices to produce an alignment. We evaluate our approach by applying it on synthetic networks and use it to de-anonymize a multimodal transportation network." @default.
- W2605118527 created "2017-04-14" @default.
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- W2605118527 date "2017-03-01" @default.
- W2605118527 modified "2023-09-26" @default.
- W2605118527 title "Multimodal Network Alignment." @default.
- W2605118527 hasPublicationYear "2017" @default.
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