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An unofficial implementation of JWNMF: "A Joint Weighted Nonnegative Matrix Factorization Model via Fusing Attribute Information for Link Prediction"

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JWNMF

This is an Unofficial implementation of method proposed by Tang in [1].

Sample Data

In this repository, we've placed a test data which is a sythensized graph generated using method proposed in [2] and simulated cascades of posts exchanged between social network nodes. Underlying graph in this data has 100 nodes and we've simulated 200 i.i.d. cascades on that. To use this to for testing proposed method in [1], we've randomly deleted some links and cascade participations.

How to run

Convert data

python converter/convert.py -d <dataset>

Run Code

python main.py -d <dataset>

Parameters

References

[1] Tang, M. (2022). A Joint Weighted Nonnegative Matrix Factorization Model via Fusing Attribute Information for Link Prediction. In: Chenggang, Y., Honggang, W., Yun, L. (eds) Mobile Multimedia Communications. MobiMedia 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 451. Springer, Cham. https://doi.org/10.1007/978-3-031-23902-1_15

[2] Lancichinetti, A., Fortunato, S., & Radicchi, F. (2008). Benchmark graphs for testing community detection algorithms. Physical review E, 78(4), 046110.

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An unofficial implementation of JWNMF: "A Joint Weighted Nonnegative Matrix Factorization Model via Fusing Attribute Information for Link Prediction"

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