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Node aggregation for enhancing PageRank

 

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Author: Maestre Torreblanca, José María
Ishii, Hideaki
Algaba Durán, Encarnación
Department: Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
Universidad de Sevilla. Departamento de Matemática Aplicada II (ETSI)
Date: 2017
Published in: IEEE Access, 5, 19799-19811.
Document type: Article
Abstract: In this paper, we study the problem of node aggregation under different perspectives for increasing PageRank of some nodes of interest. PageRank is one of the parameters used by the search engine Google to determine the relevance of a web page. We focus our attention to the problem of nding the best nodes in the network from an aggregation viewpoint, i.e., what are the best nodes to merge with for the given nodes. This problem is studied from global and local perspectives. Approximations are proposed to reduce the computation burden and to overcome the limitations resulting from the lack of centralized information. Several examples are presented to illustrate the different approaches that we propose
Cite: Maestre, J.M., Ishii, H. y Algaba, E. (2017). Node aggregation for enhancing PageRank. IEEE Access, 5, 19799-19811.
Size: 4.691Mb
Format: PDF

URI: https://hdl.handle.net/11441/70982

DOI: 10.1109/ACCESS.2017.2750700

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