LinkBlackHole*: Robust Overlapping Community Detection Using Link Embedding (Extended Abstract)

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 123
  • Download : 0
This paper proposes LinkBlackHole', a novel algorithm for finding communities that are (i) overlapping in nodes and (ii) mixing (not separating clearly) in links. There has been a small body of work in each category, but this paper is the first one that addresses both. For this purpose, LinkBlackHole incorporates the advantages of both the link -space transformation and the black hole transformation. Thorough experiments show superior quality of the communities detected by LinkBlackHole* to those detected by other state-of-the-art algorithms.
Publisher
IEEE
Issue Date
2019-04-09
Language
English
Citation

35th IEEE International Conference on Data Engineering (ICDE 2019), pp.2123 - 2124

DOI
10.1109/ICDE.2019.00256
URI
http://hdl.handle.net/10203/263491
Appears in Collection
IE-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0