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Promise

A tensor decomposition technique that can be used for link prediction in a dynamic graph. Focus on 3 dimensions (third-order tensor), where the first two can be the adjacency matrix and the third the time.

Practical results come from the CP (CanDecomp /ParaFac) technique, which is an approximation of the tensor decomposition.

Simple, effective.

Delivery

Simply written, delivers as promised.

Good introduction to tensor decomposition.

Supports dynamic graphs, but only in time: number of users or items doesn't change - only the connections between them.

No extensions about adding/deleting nodes either.

Last changed by 
 
Giorgos Georgiadis
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Link prediction

Generic method Using participant-votes data, it is possible to predict future votes as follows: Use a tensor to store participant-votes data, one slice per positive/negative/pass votes. Use modified tensor decomposition such as CP to derive latent matrices, as follows: When updating the elements of the latent matrices, evaluate their fitness using a weight matrix. The weight elements should be 1 when the observation is present in the same place in participant-votes data 0 when the observation is missing (i.e. link to be predicted)

Jan 31, 2021
Stochastic block models

title Pol.is Analysis / Stochastic block models description Stochastic block models https://arxiv.org/abs/1501.06444 Stochastic block models for multiplex networks  can give you the probability that a given node belongs to a given cluster/block over all 3 layers (agree/pass/disagree), without squishing the different relationships into one. > home

Jan 31, 2021
Multiplex layer distance

title Pol.is Analysis / Multiplex layer distance description Multiplex layer distance https://iopscience.iop.org/article/10.1088/1367-2630/ab14b3 Here the authors suggest that if you use any type of centrality measure in each network layer (e.g. degree centrality for the positive-answers layer and 'inverse degree' centrality for the negative-answers) but convert it into 'rank'... ... you can work in a unifying way over all layers and eg define a sort of distance  between them.

Jan 31, 2021
Related Literature

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Jan 31, 2021
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