Link Prediction in Multiplex Networks based on Interlayer Similarity

by   Shaghayegh Najari, et al.

Some networked systems can be better modelled by multilayer structure where the individual nodes develop relationships in multiple layers. Multilayer networks with similar nodes across layers are also known as multiplex networks. This manuscript proposes a novel framework for predicting forthcoming or missing links in multiplex networks. The link prediction problem in multiplex networks is how to predict links in one of the layers, taking into account the structural information of other layers. The proposed link prediction framework is based on interlayer similarity and proximity-based features extracted from the layer for which the link prediction is considered. To this end, commonly used proximity-based features such as Adamic-Adar and Jaccard Coefficient are considered. These features that have been originally proposed to predict missing links in monolayer networks, do not require learning, and thus are simple to compute. The proposed method introduces a systematic approach to take into account interlayer similarity for the link prediction purpose. Experimental results on both synthetic and real multiplex networks reveal the effectiveness of the proposed method and show its superior performance than state-of-the-art algorithms proposed for the link prediction problem in multiplex networks.



There are no comments yet.


page 11


Predicting missing links via correlation between nodes

As a fundamental problem in many different fields, link prediction aims ...

DeepLink: A Novel Link Prediction Framework based on Deep Learning

Recently, link prediction has attracted more attentions from various dis...

A Hidden Challenge of Link Prediction: Which Pairs to Check?

The traditional setup of link prediction in networks assumes that a test...

Who will accept my request? Predicting response of link initiation in two-way relation networks

Popularity of social networks has rapidly increased over the past few ye...

Tensorial and bipartite block models for link prediction in layered networks and temporal networks

Many real-world complex systems are well represented as multilayer netwo...

Stacking Models for Nearly Optimal Link Prediction in Complex Networks

Most real-world networks are incompletely observed. Algorithms that can ...

Multilayer Networks for Text Analysis with Multiple Data Types

We are interested in the widespread problem of clustering documents and ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.