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Link Prediction in Social Networks

Part of the SpringerBriefs in Computer Science Book Series

DOI: 10.1007/978-3-319-28922-9

ISBN: 978-3-319-28921-2

Publisher: Springer International Publishing - Springer Journals

Jan 23, 2016

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Introduction

Srinivas, Virinchi; Mitra, Pabitra

Pages: 1 –14

[Link prediction deals with predicting new links which are likely to emerge in network in the future, given the network at the current time. It has a wide range of applications including recommender systems, spam mail classification, identifying domain experts in various research areas, etc. In...
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Link Prediction Using Thresholding Nodes Based on Their Degree

Srinivas, Virinchi; Mitra, Pabitra

Pages: 15 –25

[In this chapter, we propose MIDT, a degree threshold-based similarity measure, for link prediction which exploits the power law degree distribution which social networks typically follow. We show that, in power law networks, the number of high-degree common neighbors is insignificant compared to...
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Locally Adaptive Link Prediction

Srinivas, Virinchi; Mitra, Pabitra

Pages: 27 –44

[In this chapter, we address the shortcomings of the existing link prediction similarity measures; every similarity measure assigns the same weight to a node irrespective of the pair of nodes between which the similarity is being computed. In contrast, the weight of a node must depend based on...
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Two-Phase Framework for Link Prediction

Srinivas, Virinchi; Mitra, Pabitra

Pages: 45 –55

[In this chapter, we focus only on link prediction in sparse networks. Link prediction in sparse networks poses a major challenge as link prediction similarity measures perform poorly on sparse networks (Eur. Phys. J. B, 85(1):3, 2012, [2]). Similar work has been done earlier in link prediction...
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Applications of Link Prediction

Srinivas, Virinchi; Mitra, Pabitra

Pages: 57 –61

[Link prediction has a wide variety of applications. Graphs provide a natural abstraction to represent interactions between different entities in a network. We can have graphs representing social networks, transportation networks, disease networks, email/telephone calls network to list a few....
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Conclusion

Srinivas, Virinchi; Mitra, Pabitra

Pages: 63 –64

[Link prediction problem has been studied extensively in relation to various applications. However, the role of degree distribution of the networks have not been explicitly exploited in this context. In this book, we deal with link prediction by considering the power law degree distribution of...

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