Link prediction in bipartite graphs using internal links and weighted projection

Oussama Allali 1 Clémence Magnien 1 Matthieu Latapy 1
1 ComplexNetworks
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : Many real-world complex networks, like client-product or file-provider relations, have a bipartite nature and evolve during time. Predicting links that will appear in them is one of the main approach to understand their dynamics. Only few works address the bipartite case, though, despite its high practical interest and the specific challenges it raises. We define in this paper the notion of internal links in bipartite graphs and propose a link prediction method based on them. We describe the method and experimentally compare it to a basic collaborative filtering approach. We present results obtained for two typical practical cases. We reach the conclusion that our method performs very well, and that internal links play an important role in bipartite graphs and their dynamics.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01286948
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Submitted on : Friday, March 11, 2016 - 3:34:55 PM
Last modification on : Thursday, March 21, 2019 - 2:16:20 PM

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Oussama Allali, Clémence Magnien, Matthieu Latapy. Link prediction in bipartite graphs using internal links and weighted projection. Third International Workshop on Network Science for Communication Networks (Netscicom 2011), In Conjuction with IEEE Infocom 2011., Apr 2011, Shanghai, China. pp.936-941, ⟨10.1109/INFCOMW.2011.5928947⟩. ⟨hal-01286948⟩

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