Projects per year
Abstract
We introduce a ranking model for temporal multidimensional weighted and directed networks based on the Perron eigenvector of a multi-homogeneous order-preserving map. The model extends to the temporal multilayer setting the HITS algorithm and defines five centrality vectors: two for the nodes, two for the layers, and one for the temporal stamps. Nonlinearity is introduced in the standard HITS model in order to guarantee existence and uniqueness of these centrality vectors for any network, without any requirement on its connectivity structure. We introduce a globally convergent power iteration like algorithm for the computation of the centrality vectors. Numerical experiments on real-world networks are performed in order to assess the effectiveness of the proposed model and showcase the performance of the accompanying algorithm.
Original language | English |
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Title of host publication | SIAM International Conference on Data Mining, SDM 2019 |
Place of Publication | Philadelphia, PA |
Pages | 369-377 |
Number of pages | 9 |
ISBN (Electronic) | 9781611975673 |
DOIs | |
Publication status | Published - 4 May 2019 |
Event | SIAM International Conference on Data Mining 2019 - Calgary, Canada Duration: 2 May 2019 → 4 May 2019 |
Conference
Conference | SIAM International Conference on Data Mining 2019 |
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Abbreviated title | SDM19 |
Country/Territory | Canada |
City | Calgary |
Period | 2/05/19 → 4/05/19 |
Keywords
- perron eigenvector
- HITS
- ranking model
Fingerprint
Dive into the research topics of 'Multi-dimensional, multilayer, nonlinear and dynamic HITS'. Together they form a unique fingerprint.Profiles
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MAGNET: Models and algorithms for graph analysis
Tudisco, F. & Higham, D.
1/07/17 → …
Project: Research Fellowship
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Don't look back -- non-backtracking walks in complex networks (ECF)
1/05/19 → 30/04/22
Project: Research Fellowship