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Erschienen in:
Human Action Recognition Using Trajectory-Based Spatiotemporal Descriptors Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Neighborhood Topology to Discover Influential Nodes in a Complex Network

verfasst von : Chandni Saxena, M. N. Doja, Tanvir Ahmad

Erschienen in: Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications

Verlag: Springer Singapore

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Abstract

This paper addresses the issue of distinguishing influential nodes in the complex network. The k-shell index features embeddedness of a node in the network based upon its number of links with other nodes. This index filters out the most influential nodes with higher values for this index, however, fails to discriminate their scores with good resolution, hence results in assigning same scores to the nodes belonging to same k-shell set. Extending this index with neighborhood coreness of a node and also featuring topological connections between its neighbors, our proposed method can express the nodes influence score precisely and can offer distributed and monotonic rank orders than other node ordering methods.

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Vorheriges Kapitel On the Security of Chaos-Based Watermarking Scheme for Secure Communication
Nächstes Kapitel Venn Diagram-Based Feature Ranking Technique for Key Term Extraction
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Metadaten
Titel
Neighborhood Topology to Discover Influential Nodes in a Complex Network
verfasst von
Chandni Saxena
M. N. Doja
Tanvir Ahmad
Copyright-Jahr
2017
Verlag
Springer Singapore
Buch
Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications

Print ISBN: 978-981-10-3152-6

Electronic ISBN: 978-981-10-3153-3

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-981-10-3153-3_32

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