Finding Tiny Clusters in Bipartite Graphs
Author:
Abstract
We study the problem of finding clusters in random bipartite graphs. Applications of this problem include online shops in which one wants to find customers who purchase similar products and groups of products which are frequently bought together. We present a simple two-step algorithm which provably finds tiny clusters of size O(n" ), where n is the number of vertices in the graph and " > 0; previous algorithms were only able to identify medium-sized clusters consisting of at least (pn) vertices. We practically evaluate the algorithm on synthetic and on real-world data; the experiments show that the algorithm can find extremely small clusters even when the graphs are very sparse and the data contains a lot of noise.
- Citation
- BibTeX
Neumann, S.,
(2019).
Finding Tiny Clusters in Bipartite Graphs.
In:
David, K., Geihs, K., Lange, M. & Stumme, G.
(Hrsg.),
INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft.
Bonn:
Gesellschaft für Informatik e.V..
(S. 253-254).
DOI: 10.18420/inf2019_30
@inproceedings{mci/Neumann2019,
author = {Neumann, Stefan},
title = {Finding Tiny Clusters in Bipartite Graphs},
booktitle = {INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft},
year = {2019},
editor = {David, Klaus AND Geihs, Kurt AND Lange, Martin AND Stumme, Gerd} ,
pages = { 253-254 } ,
doi = { 10.18420/inf2019_30 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
author = {Neumann, Stefan},
title = {Finding Tiny Clusters in Bipartite Graphs},
booktitle = {INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft},
year = {2019},
editor = {David, Klaus AND Geihs, Kurt AND Lange, Martin AND Stumme, Gerd} ,
pages = { 253-254 } ,
doi = { 10.18420/inf2019_30 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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More Info
DOI: 10.18420/inf2019_30
ISBN: 978-3-88579-688-6
ISSN: 1617-5468
xmlui.MetaDataDisplay.field.date: 2019
Language:
(en)

Content Type: Text/Conference Paper