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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

6. Real-World Cases of Network Structure Analytics

verfasst von : Maoguo Gong, Qing Cai, Lijia Ma, Shanfeng Wang, Yu Lei

Erschienen in: Computational Intelligence for Network Structure Analytics

Verlag: Springer Singapore

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Abstract

In complex systems, except for the issues discussed in previous chapters, the issues, including recommender system, network alignment and influence maximization etc. are also NP-hard problems, and they can be modeled as optimization problems. Computational intelligence algorithms, especially evolutionary algorithms, have been successfully employed to these network structure analytics topics. In this chapter, we will present how to use computational intelligence techniques to tackle the recommendation system, the network alignment, and the influence maximization problem in complex networks. First, an evolutionary multiobjective algorithm is used for recommendation. And then, a memetic algorithm for influence maximization is introduced. Finally, a memetic algorithm for global biological network alignment is presented.

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Vorheriges Kapitel Network Robustness Analytics with Optimization
Nächstes Kapitel Concluding Remarks
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Metadaten
Titel
Real-World Cases of Network Structure Analytics
verfasst von
Maoguo Gong
Qing Cai
Lijia Ma
Shanfeng Wang
Yu Lei
Copyright-Jahr
2017
Verlag
Springer Singapore
Buch
Computational Intelligence for Network Structure Analytics

Print ISBN: 978-981-10-4557-8

Electronic ISBN: 978-981-10-4558-5

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-981-10-4558-5_6

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